Plan meticulously before launching a business intelligence (BI) project. Brief the senior managers while implementing a BI application project so they can back the information technology department's plans. This way, the team remains cohesive and goal-oriented. In addition, the IT managers, MIS directors, and chief information officers should carefully assemble the right team for implementation and select the right business intelligence product.
Establish the Need
Management and business community must have a general understanding and appreciation of the value that business intelligence applications can provide. Create a compelling need for developing a business intelligence application within your organization. Company individuals can use it to access data to obtain specific information or use it to solve any type of business problems. Plan your project thoroughly before implementing it, and complete the project within the stipulated time frame.
Develop a Formal Project Plan
Your plan is a living document that must be updated continually through the life of the project. It is a reference document to all the project details and helps to manage the expectations and outcome of the final delivery. The plan should contain:
Business requirements
Scope and delivery
Critical success factors
User acceptance criteria
Tasks
Timeline
Roles and responsibilities
Proper planning leads to a successful BI project in which all of organization's expectations are met or exceeded. Formally documenting and communicating the deliveries help to fulfill user expectations.
Checklist for BI Planning
To ensure the success of your business intelligence project planning and implementation, use the following checklist:
Define the project
Identify the users
Develop a formal project plan
Assemble the project team
Assess all information and technical needs
Select the software
Configure the business intelligence application
Deploy a support strategy
Train all users
Ensuring Success
Present your business intelligence strategy to someone you report to before implementation. Give a presentation to the executive committee on the expenditures, data restructuring, overhauls, incremental expenses, requirement of skilled manpower, ramifications and effect on the enterprise. This will provide a nucleus to work with and develop or implement a well-planned BI project. Follow the following checklist to ensure success:
Have a corporate BI mission statement.
Have a centralized managed approach.
End user and IT representatives should meet regularly.
Justify BI acquisitions with RFI/RFP, specific application, end-user surveys and requests, IT decisions with use input.
Evaluate criteria and measurement processes to track BI efforts in place.
Have a formal model of BI support structure in place.
For end-user input requirements, allow individual departments and functional areas to select and maintain their own BI strategies.
Publish an approved BI strategy document describing all selections in details for future references.
Review the necessary documents periodically.
Take steps and spend time to plan your business intelligence initiative to avoid business failure. Goals and organizational aspirations cannot be achieved without a plan. A proper plan enthuses the project team to aim for success within a given time frame and with an optimal use of resources.
Sunday, November 27, 2011
Friday, November 25, 2011
Ten Reasons Why Business Intelligence Is Different From Other Applications
Business and IT professionals who have a variety of experience with different applications, like CRM, ERP, LMS, HRM, and SCM, tend to think that Business Intelligence (BI) is just another, similar application. However, BI offers opportunities for businesses that far outshine other narrowly focused software solutions - most notably through its vast scope, comprehensive reporting tools, and diverse scalability. Here are 10 attributes that separate BI from the rest:
1. BI Is User-Defined and Scalable
If you ask a group of people to define CRM or other application terms, there's a good chance that all of their definitions will be quite similar. However, if you ask them to define Business Intelligence, you'll likely hear reporting tools, analytics, dashboards, scorecards, data modeling, data warehouse, data mining, online analytical processing (OLAP), or performance management. It is all of those, and more.
2. The BI Market Is Saturated
Because Business Intelligence offers such diverse opportunities, the marketplace is full of vendors claiming to sell "BI" solutions. When searching and evaluating different products, it's easy to get lost in the myriad of features and functions. Each product may do some things, but not necessarily all of them; however BI can deliver many, if not all of them. When considering a BI platform, it's important to learn about BI's many embedded features and create a prioritized list for your own organization.
3. BI's Feature Set Is Complex
Compared to standard business software applications, Business Intelligence has many more features that can present a challenge to learn. This initial learning can include drilling down to a report, adding summarizations, or learning the best way to display data visually. For example, in data mining you may need to learn about clustering, decision trees, or regression, all-powerful features that require a higher learning curve than out-of-the box solutions. However, BI's benefits do outweigh the difficulties.
4. It's Horizontal, Not Vertical
Business Intelligence platforms take a horizontal approach to data that supports many vertical applications - including most of those listed above in item number one. Every organization or application with data has a potential case for using BI, no matter how many vertical uses or applications might be involved.
5. BI's Data Structure Is Flexible
Data that is stored and used for Business Intelligence can be either standardized for transactional systems or optimized for reporting and analysis. BI is flexible and can provide good results using many different structures. Although most business applications rely on transactional structures for speedy record processing, in BI it can be modeled as relational, dimensional, or a hybrid that might be ROLAP (Relational) or MOLAP (Multidimensional).
6. BI Is a Platform, Not a "Solution"
It's important to understand the difference. Most business applications are available as software solutions-fit for specific purposes and ready to use right out of the box. Most Business Intelligence applications rely on platforms where technical users build specific solutions in a development environment. There are a few BI vendors who are moving toward solution-based applications.
7. BI Requires IT Involvement
Because Business Intelligence is complex, flexible in structure, and platform-based, it depends more on IT than most business applications. Organizations where business users and IT resources work together will experience a much greater overall success rate with Business Intelligence.
8. Software As A Service (SaaS) Is Immature
SaaS can now be considered a viable solution for many business applications. Salesforce.com, for example, has a proven track record of success. However, that is not the case for BI. While it is appealing and there are a few SaaS entrants, it's just not plug-n-play as some vendors might tell you. There is still the upfront and ongoing work of data integration, data cleansing, data modeling, and data refreshes. Until the market matures, it will be difficult to realize the significant benefits of SaaS for BI.
9. User Adoption Can Be Challenging
Most business applications are specific to standard business processes-something users are already comfortable with. However, Business Intelligence is very flexible and doesn't follow any specific, prescribed process. Users have the ability to explore the data and develop reporting tools as they choose. This is a huge benefit that can also present challenges and intimidate many users preventing them from fully adopting a BI solution.
10. BI Has Only 2 Letters!
Other application abbreviations have 3 letters. So...BI is one-third easier to remember. OK, we had to throw in something fun about Business Intelligence!
1. BI Is User-Defined and Scalable
If you ask a group of people to define CRM or other application terms, there's a good chance that all of their definitions will be quite similar. However, if you ask them to define Business Intelligence, you'll likely hear reporting tools, analytics, dashboards, scorecards, data modeling, data warehouse, data mining, online analytical processing (OLAP), or performance management. It is all of those, and more.
2. The BI Market Is Saturated
Because Business Intelligence offers such diverse opportunities, the marketplace is full of vendors claiming to sell "BI" solutions. When searching and evaluating different products, it's easy to get lost in the myriad of features and functions. Each product may do some things, but not necessarily all of them; however BI can deliver many, if not all of them. When considering a BI platform, it's important to learn about BI's many embedded features and create a prioritized list for your own organization.
3. BI's Feature Set Is Complex
Compared to standard business software applications, Business Intelligence has many more features that can present a challenge to learn. This initial learning can include drilling down to a report, adding summarizations, or learning the best way to display data visually. For example, in data mining you may need to learn about clustering, decision trees, or regression, all-powerful features that require a higher learning curve than out-of-the box solutions. However, BI's benefits do outweigh the difficulties.
4. It's Horizontal, Not Vertical
Business Intelligence platforms take a horizontal approach to data that supports many vertical applications - including most of those listed above in item number one. Every organization or application with data has a potential case for using BI, no matter how many vertical uses or applications might be involved.
5. BI's Data Structure Is Flexible
Data that is stored and used for Business Intelligence can be either standardized for transactional systems or optimized for reporting and analysis. BI is flexible and can provide good results using many different structures. Although most business applications rely on transactional structures for speedy record processing, in BI it can be modeled as relational, dimensional, or a hybrid that might be ROLAP (Relational) or MOLAP (Multidimensional).
6. BI Is a Platform, Not a "Solution"
It's important to understand the difference. Most business applications are available as software solutions-fit for specific purposes and ready to use right out of the box. Most Business Intelligence applications rely on platforms where technical users build specific solutions in a development environment. There are a few BI vendors who are moving toward solution-based applications.
7. BI Requires IT Involvement
Because Business Intelligence is complex, flexible in structure, and platform-based, it depends more on IT than most business applications. Organizations where business users and IT resources work together will experience a much greater overall success rate with Business Intelligence.
8. Software As A Service (SaaS) Is Immature
SaaS can now be considered a viable solution for many business applications. Salesforce.com, for example, has a proven track record of success. However, that is not the case for BI. While it is appealing and there are a few SaaS entrants, it's just not plug-n-play as some vendors might tell you. There is still the upfront and ongoing work of data integration, data cleansing, data modeling, and data refreshes. Until the market matures, it will be difficult to realize the significant benefits of SaaS for BI.
9. User Adoption Can Be Challenging
Most business applications are specific to standard business processes-something users are already comfortable with. However, Business Intelligence is very flexible and doesn't follow any specific, prescribed process. Users have the ability to explore the data and develop reporting tools as they choose. This is a huge benefit that can also present challenges and intimidate many users preventing them from fully adopting a BI solution.
10. BI Has Only 2 Letters!
Other application abbreviations have 3 letters. So...BI is one-third easier to remember. OK, we had to throw in something fun about Business Intelligence!
Wednesday, November 23, 2011
How to Choose The Best Business Intelligence Solution For Microsoft Dynamics AX
Business Intelligence for Dynamics AX - What is the Best Solution?
This question will be asked every day by thousands of Dynamics AX users and many of their AX partners. There is not one answer to this question as it really depends on many factors like size of the company, do you already use a kind of BI tool, your preferred platform like SQL Server or Oracle and many more. Without any doubt, a Business Intelligence Solution without an underlying data warehouse is doomed for problems, at least in the long run. Some of your options are:
1. Build your own data warehouse and Business Intelligence Solution with Microsoft BIDS
2. Use embedded Business Intelligence by Microsoft in Dynamics AX
3. Purchase a pre-packaged Business Intelligence Solution which is tailored for Dynamics AX
4. Purchase a drag and drop data warehouse tool which auto-generates your SQL code and also builds your OLAP cubes and select an Analysis tool of your choice.
A few comments to these four options:
Microsoft BIDS (Business Intelligence Development Studio) is a great development environment for SQL Server experts to create a SQL Server based data warehouse and OLAP cubes. So if you have the experts in-house and want to spend the time and money, this is an option, but be aware of the complexity of BIDS, the time it takes to create a BI solution with it and the dependency on these experts, either in your own company or externally.
Microsoft Dynamics AX offers pre-packaged BI components like OLAP cubes for a variety of AX modules. But be aware that they are not based on a true data warehouse which means any integration of external data sources or changes in dimensions/measures/KPI's is possible, but complicated and needs experts again. It is generally not a good idea to integrate Business Intelligence into ERP. There are many pre-defined Dynamics Business Intelligence Solutions around, like ZAP, iQ4bis, Profitbase, Brio, Qlikview, Targit and many more. All of them have their benefits to implement a BI solution for Dynamics relatively fast. The only reservation I have is, that they either don't offer a true data warehouse as the underlying technology forces you to use their propriety front-end tool or both. The price difference for these tools varies from $15,000 to $100,000+
In my opinion, option 4 of the above list will give you the best results and highest flexibility. There are not a lot of tools around which helps you to create a flexible and ERP independent data warehouse and also creates the OLAP cubes with little effort and is front-end agnostic. Why not start with technology you already use like SQL Server, Excel and SharePoint and then look into Analytics tool later.
This question will be asked every day by thousands of Dynamics AX users and many of their AX partners. There is not one answer to this question as it really depends on many factors like size of the company, do you already use a kind of BI tool, your preferred platform like SQL Server or Oracle and many more. Without any doubt, a Business Intelligence Solution without an underlying data warehouse is doomed for problems, at least in the long run. Some of your options are:
1. Build your own data warehouse and Business Intelligence Solution with Microsoft BIDS
2. Use embedded Business Intelligence by Microsoft in Dynamics AX
3. Purchase a pre-packaged Business Intelligence Solution which is tailored for Dynamics AX
4. Purchase a drag and drop data warehouse tool which auto-generates your SQL code and also builds your OLAP cubes and select an Analysis tool of your choice.
A few comments to these four options:
Microsoft BIDS (Business Intelligence Development Studio) is a great development environment for SQL Server experts to create a SQL Server based data warehouse and OLAP cubes. So if you have the experts in-house and want to spend the time and money, this is an option, but be aware of the complexity of BIDS, the time it takes to create a BI solution with it and the dependency on these experts, either in your own company or externally.
Microsoft Dynamics AX offers pre-packaged BI components like OLAP cubes for a variety of AX modules. But be aware that they are not based on a true data warehouse which means any integration of external data sources or changes in dimensions/measures/KPI's is possible, but complicated and needs experts again. It is generally not a good idea to integrate Business Intelligence into ERP. There are many pre-defined Dynamics Business Intelligence Solutions around, like ZAP, iQ4bis, Profitbase, Brio, Qlikview, Targit and many more. All of them have their benefits to implement a BI solution for Dynamics relatively fast. The only reservation I have is, that they either don't offer a true data warehouse as the underlying technology forces you to use their propriety front-end tool or both. The price difference for these tools varies from $15,000 to $100,000+
In my opinion, option 4 of the above list will give you the best results and highest flexibility. There are not a lot of tools around which helps you to create a flexible and ERP independent data warehouse and also creates the OLAP cubes with little effort and is front-end agnostic. Why not start with technology you already use like SQL Server, Excel and SharePoint and then look into Analytics tool later.
Saturday, November 19, 2011
Project Analytics Using Oracle Business Intelligence
Knowledge is Power. This adage holds true now more than ever. Everyone is looking for fast and reliable information to help them make timely informed decisions. In the olden days information was filtered down to masses in a gradual manner. It took time for information, good or bad, to propagate.
Fast forward to today, the progress in information technology is nothing short of a revolution. People are exposed to the 24 Hour Cycle. It takes only a few minutes for an event happening in a particular part of the World to appear on TV screens and Web Pages across the World.
'Analytics' has been defined as the 'science of analysis'. In the Corporate World, Information has itself become 'commoditized'. Big bucks are spent to gather and 'buy' Information. Fast and reliable information is scarce. Insight out of the information is even scarcer. Big retail firms spend millions on market research of not only their own Products but those of their competitors as well. The research firms gather the data and present their results back to the Managers to 'Analyze' and act upon. Crude oil and oil futures are traded publicly. The daily output from OPEC is limited and is public knowledge. The Refining capacity for each country is generally flat. So why does an investor pay more for a future contract of Crude Oil than others? Maybe he knows more than the other investors, or maybe even less. A number of Energy Analysts look at all sorts of data related to the Production, Transportation, Refining and Consumption of Oil. They look at everything from delays in shipping lanes and unrest in Oil producing regions to weather patterns around rigs and consumption trends. Their job is to gather, refine and deliver the data to the investors to help them make an intelligent and informed decision in a timely manner.
The decision makers do not necessarily want all the minute details. What they need is the 'Analytics' support provided by the Analysts. They need the insight from all the data and information. It is this fast and accurate access to this actionable insight that helps companies and investors out maneuver and beat their competitors.
Business leaders have started to realize the benefits of automated software based Business Analytics in gathering information on their operations, production and transactional activities. Businesses are deploying Analytics applications that automate the information gathering and presentation. There has been increasing demand for Analytics support in a number of additional areas. One of the areas is Project Management.
A number of Enterprise resource planning 'ERP' Systems offer applications related to Project Management. Each ERP system offers a handful of tools in their Project Management application that differentiate them from each other. An increasing number of mid-size to large and even some small companies are deploying Project Management Applications.
ERP systems at the core help the company manage their assets, resources and most importantly their finances. As Project Management evolved and standardized in the last decade thanks to professionals and organizations like the PMI, the Industry realized the benefits of managing the progress and finances of their individual projects separately from their production /day to day management.
The Project Management modules in the ERP systems provide the functionality to itemize, track and manage the Project Related transactions for the company. As the Project Management module is tied to the Financials Module, the Project Manager can easily manage the Funding, Invoices, Journals, Revenue recognition and the costs associated with each individual project. The reporting and analytics capabilities in these Business Applications are however limited.
Oracle is first major software company to release a comprehensive Project Analytics suite. They have released Project Analytics as part of their Oracle Business Intelligence Enterprise Edition 7.9.6 Release. The Project Analytics Module sources raw Project Data from Oracle EBS and PeopleSoft Enterprise Project Management Applications. It extracts and refines the data into reports and presents the refined data on the Analytics Dashboard. The web based Dashboards provide graphical and tabular representation of customizable data. Oracle Project Analytics displays Project reports related to Project cost, revenue, budget and billing among other things.
In Today's recessionary environment the CIOs and CEOs are actively looking at ways of reducing costs and maximizing the revenue with limited resources. Oracle Project Analytics provides essential project based metrics on web based dashboards. The information is clearly laid out and gives fast fact based visibility into the Project Performance.
Anyone having access to the Dashboard, from Developers to Project Managers to the CEO can look at the insight provided by Oracle Project Analytics and act quickly and decisively to adjust resources, reduce costs and increase profitability. This comes with a prebuilt Dashboard and Data Warehouse, but the users have the ability to create custom reports and metrics in the Dashboard.
The Dashboards have role based access. The Administrators have the capability to grant access to users based on their roles within the organization. The level of access can also be controlled. A Project member can have Read access only while the Project Manager may have full edit access to the same report or dashboard.
After login the CEO may be taken to the Executive Dashboard with high level metrics for active Projects across his Organization. The Executive can go through the metrics, quickly identify the areas needing his attention and drill down to the detail level for further information.
Other individuals may be denied access to the Executive Dashboard and taken to their customized dashboard. This is extremely important because it gives the users only the information that they need very quickly. The managers do not have to sift through data and turn over pages to get what they want. The Project manager can quickly identify and address the cost variance issue in the project while the Organization Director is in a better position to move resources between projects after going through the Dashboard metrics. It helps the user make informed decisions in a timely manner.
Typically the Project financial data and status is entered into the Project Management ERP Applications by Project Managers, project team members and accountants. Working with these applications requires a level of expertise that a typical management team does not have. These applications provide a good mechanism of project management but lack the reporting flexibility. Reports are generally created though the ERP applications at the Project or Organization level. Management feeds these numbers in their spreadsheets for management review. There are a few problems with this approach. Firstly there is quite a bit of manual work and calculation required which may be prone to human errors. Secondly by the time the report filters up to the Executives it might already be too late to act.
Since the warehouse behind the dashboard is sourced from the same ERP application that the Project Team enters data into, the executives can access their favorite reports on the dashboard promptly and not worry about the accuracy of the data. This is the fundamental benefit of the fast fact based Analytics.
The Project Analytics data is currently sourced from Oracle E-Business Suite and the Oracle's PeopleSoft Enterprise ERP Applications. A universal adapter is also provided which can be used by the administrators to fetch and display Project data from other Source Systems.
The data in Project Analytics is tightly coupled with General Ledger and Financials data from the Source System. The users can view the Key Progress Indicators for the Projects against the General Ledger, Accounts receivables and Accounts Payables data.
One big incentive to the Managers is the implementation and maintenance cost associated with Oracle Project analytics. The Warehouse and Dashboard associated with Oracle Project Analytics is tightly integrated with existing Oracle EBS and PeopleSoft Enterprise Applications. The Warehouse is supported on multiple Databases and can be hosted on an existing Databases Server having sufficient space and memory.
The setup and administration is not overly complicated. Anyone having Database administration expertise and some web administration experience should be able to manage the administration. This helps keep the training costs in check while also leveraging the skills of the existing workforce.
Creating the custom reports and graphs using the Dashboard seems intuitive. The primary users of the Analytics dashboards are Company managers with limited SQL skills. The Project Analytics dashboard was designed with this in mind. The users can create their own custom reports and graphs with relative ease. They save these metrics on their dashboard and even make them available for others to view.
Project Analytics gives the Management team the ability to view the historical Project data. They can thus make better informed decisions and can browse the metrics for trending and forecasting.
Alerts are another useful feature of the Oracle Business Intelligence Enterprise Edition that Project Analytics can leverage. The users can add custom alerts on metrics. Let's say that a Manager wants to be notified whenever a threshold on cost variance or unrealized Revenue has reached. The manager can set the value on the appropriate report and an Alert will show up at his next login after the alert condition is met. Furthermore, the Alert system can also be configured to send an email to the user whenever the alert condition is met. He can receive the alert notification on his personal computer or the handheld device and take the necessary action.
Although the data in the Warehouse may be sourced from one or more ERP systems at the back end, the front end i.e. the Dashboard is hosted as web interface. So there is no bulky install required on the end user's machine and more importantly the metrics are available on any device with internet browser support. Typically anyone with access to the corporate Intranet can access the metrics on the personal computing device of their choice. A General Manager in Brussels can access the Project metrics for the big construction project in Boston just before his big meeting with the Board.
Fast forward to today, the progress in information technology is nothing short of a revolution. People are exposed to the 24 Hour Cycle. It takes only a few minutes for an event happening in a particular part of the World to appear on TV screens and Web Pages across the World.
'Analytics' has been defined as the 'science of analysis'. In the Corporate World, Information has itself become 'commoditized'. Big bucks are spent to gather and 'buy' Information. Fast and reliable information is scarce. Insight out of the information is even scarcer. Big retail firms spend millions on market research of not only their own Products but those of their competitors as well. The research firms gather the data and present their results back to the Managers to 'Analyze' and act upon. Crude oil and oil futures are traded publicly. The daily output from OPEC is limited and is public knowledge. The Refining capacity for each country is generally flat. So why does an investor pay more for a future contract of Crude Oil than others? Maybe he knows more than the other investors, or maybe even less. A number of Energy Analysts look at all sorts of data related to the Production, Transportation, Refining and Consumption of Oil. They look at everything from delays in shipping lanes and unrest in Oil producing regions to weather patterns around rigs and consumption trends. Their job is to gather, refine and deliver the data to the investors to help them make an intelligent and informed decision in a timely manner.
The decision makers do not necessarily want all the minute details. What they need is the 'Analytics' support provided by the Analysts. They need the insight from all the data and information. It is this fast and accurate access to this actionable insight that helps companies and investors out maneuver and beat their competitors.
Business leaders have started to realize the benefits of automated software based Business Analytics in gathering information on their operations, production and transactional activities. Businesses are deploying Analytics applications that automate the information gathering and presentation. There has been increasing demand for Analytics support in a number of additional areas. One of the areas is Project Management.
A number of Enterprise resource planning 'ERP' Systems offer applications related to Project Management. Each ERP system offers a handful of tools in their Project Management application that differentiate them from each other. An increasing number of mid-size to large and even some small companies are deploying Project Management Applications.
ERP systems at the core help the company manage their assets, resources and most importantly their finances. As Project Management evolved and standardized in the last decade thanks to professionals and organizations like the PMI, the Industry realized the benefits of managing the progress and finances of their individual projects separately from their production /day to day management.
The Project Management modules in the ERP systems provide the functionality to itemize, track and manage the Project Related transactions for the company. As the Project Management module is tied to the Financials Module, the Project Manager can easily manage the Funding, Invoices, Journals, Revenue recognition and the costs associated with each individual project. The reporting and analytics capabilities in these Business Applications are however limited.
Oracle is first major software company to release a comprehensive Project Analytics suite. They have released Project Analytics as part of their Oracle Business Intelligence Enterprise Edition 7.9.6 Release. The Project Analytics Module sources raw Project Data from Oracle EBS and PeopleSoft Enterprise Project Management Applications. It extracts and refines the data into reports and presents the refined data on the Analytics Dashboard. The web based Dashboards provide graphical and tabular representation of customizable data. Oracle Project Analytics displays Project reports related to Project cost, revenue, budget and billing among other things.
In Today's recessionary environment the CIOs and CEOs are actively looking at ways of reducing costs and maximizing the revenue with limited resources. Oracle Project Analytics provides essential project based metrics on web based dashboards. The information is clearly laid out and gives fast fact based visibility into the Project Performance.
Anyone having access to the Dashboard, from Developers to Project Managers to the CEO can look at the insight provided by Oracle Project Analytics and act quickly and decisively to adjust resources, reduce costs and increase profitability. This comes with a prebuilt Dashboard and Data Warehouse, but the users have the ability to create custom reports and metrics in the Dashboard.
The Dashboards have role based access. The Administrators have the capability to grant access to users based on their roles within the organization. The level of access can also be controlled. A Project member can have Read access only while the Project Manager may have full edit access to the same report or dashboard.
After login the CEO may be taken to the Executive Dashboard with high level metrics for active Projects across his Organization. The Executive can go through the metrics, quickly identify the areas needing his attention and drill down to the detail level for further information.
Other individuals may be denied access to the Executive Dashboard and taken to their customized dashboard. This is extremely important because it gives the users only the information that they need very quickly. The managers do not have to sift through data and turn over pages to get what they want. The Project manager can quickly identify and address the cost variance issue in the project while the Organization Director is in a better position to move resources between projects after going through the Dashboard metrics. It helps the user make informed decisions in a timely manner.
Typically the Project financial data and status is entered into the Project Management ERP Applications by Project Managers, project team members and accountants. Working with these applications requires a level of expertise that a typical management team does not have. These applications provide a good mechanism of project management but lack the reporting flexibility. Reports are generally created though the ERP applications at the Project or Organization level. Management feeds these numbers in their spreadsheets for management review. There are a few problems with this approach. Firstly there is quite a bit of manual work and calculation required which may be prone to human errors. Secondly by the time the report filters up to the Executives it might already be too late to act.
Since the warehouse behind the dashboard is sourced from the same ERP application that the Project Team enters data into, the executives can access their favorite reports on the dashboard promptly and not worry about the accuracy of the data. This is the fundamental benefit of the fast fact based Analytics.
The Project Analytics data is currently sourced from Oracle E-Business Suite and the Oracle's PeopleSoft Enterprise ERP Applications. A universal adapter is also provided which can be used by the administrators to fetch and display Project data from other Source Systems.
The data in Project Analytics is tightly coupled with General Ledger and Financials data from the Source System. The users can view the Key Progress Indicators for the Projects against the General Ledger, Accounts receivables and Accounts Payables data.
One big incentive to the Managers is the implementation and maintenance cost associated with Oracle Project analytics. The Warehouse and Dashboard associated with Oracle Project Analytics is tightly integrated with existing Oracle EBS and PeopleSoft Enterprise Applications. The Warehouse is supported on multiple Databases and can be hosted on an existing Databases Server having sufficient space and memory.
The setup and administration is not overly complicated. Anyone having Database administration expertise and some web administration experience should be able to manage the administration. This helps keep the training costs in check while also leveraging the skills of the existing workforce.
Creating the custom reports and graphs using the Dashboard seems intuitive. The primary users of the Analytics dashboards are Company managers with limited SQL skills. The Project Analytics dashboard was designed with this in mind. The users can create their own custom reports and graphs with relative ease. They save these metrics on their dashboard and even make them available for others to view.
Project Analytics gives the Management team the ability to view the historical Project data. They can thus make better informed decisions and can browse the metrics for trending and forecasting.
Alerts are another useful feature of the Oracle Business Intelligence Enterprise Edition that Project Analytics can leverage. The users can add custom alerts on metrics. Let's say that a Manager wants to be notified whenever a threshold on cost variance or unrealized Revenue has reached. The manager can set the value on the appropriate report and an Alert will show up at his next login after the alert condition is met. Furthermore, the Alert system can also be configured to send an email to the user whenever the alert condition is met. He can receive the alert notification on his personal computer or the handheld device and take the necessary action.
Although the data in the Warehouse may be sourced from one or more ERP systems at the back end, the front end i.e. the Dashboard is hosted as web interface. So there is no bulky install required on the end user's machine and more importantly the metrics are available on any device with internet browser support. Typically anyone with access to the corporate Intranet can access the metrics on the personal computing device of their choice. A General Manager in Brussels can access the Project metrics for the big construction project in Boston just before his big meeting with the Board.
Thursday, November 17, 2011
Business Intelligence - Learn More About It
Business intelligence tools are currently used by many companies to guide them in report generation and consequently decision-making. But what is the outlook for these tools in the future? How would these tools impact those entrepreneurs who are building businesses?
In the near future, these are the following expectations for business intelligence tools:
- Cloud computing will be a great influence in terms of its simplicity. The influence of the users will also grow in terms of what new business intelligence tools would come out. The clients for these tools will demand the ease-of-use for such tools as well as the ease of its acquisition, installation and maintenance. The sellers of these business intelligence tools would thus have to adapt to the expectations of potential buyers. They would thus have to increase the speed of deployment for the products as well as the availability of purchase in smaller increments.
- Business analytics appliances would be incorporating databases including business intelligence tools with user-interfacing functions. The sellers of these products would thus have to widen their product range to include reporting and analysis tools not just tools wherein the user just inputs data. Some of these products had its debut in the market last 2011 but it is expected to be utilized by more companies in the years to come.
- The growth in the demand for mobile business intelligence tools is also projected. Clients however, are expected to look for more case-specific products rather than just generic tools. Today, many business intelligence tools makers are continuing their research on what should be the best design so that their products would fit the mobile lifestyle of their client base. They need business solutions that should give more value to the clients. The tools that would just allow the viewing, commenting and editing of a report are a thing of the past. The new generation business intelligence tools should allow for collaboration as well as workflow approvals while being mobile.
- It is also predicted that there will be more advanced analytics that will be made available in the market. Currently, there aren't enough quantitative analysts out there in the job market that could do the complex analysis required by many companies. Thus, there would be a need and also a growth on business intelligence tools that could have more of the quantitative predictive function. This is targeted to help businessmen in the analytical and decision-making process without the need of added manpower.
- There is also an expectation that knowledge management will re-surge in importance. This will thus prod business intelligence tool vendors to invest more on technologies that will support collaboration. It would also help if the collaboration tool would include social media integration.
All of these expected future developments in it would impact the business of entrepreneurs in terms of ease of decision-making. It would also bring in convenience as the mobility and social media components are factored in. Over all, these projected developments are on the plus side for business owners.
In the near future, these are the following expectations for business intelligence tools:
- Cloud computing will be a great influence in terms of its simplicity. The influence of the users will also grow in terms of what new business intelligence tools would come out. The clients for these tools will demand the ease-of-use for such tools as well as the ease of its acquisition, installation and maintenance. The sellers of these business intelligence tools would thus have to adapt to the expectations of potential buyers. They would thus have to increase the speed of deployment for the products as well as the availability of purchase in smaller increments.
- Business analytics appliances would be incorporating databases including business intelligence tools with user-interfacing functions. The sellers of these products would thus have to widen their product range to include reporting and analysis tools not just tools wherein the user just inputs data. Some of these products had its debut in the market last 2011 but it is expected to be utilized by more companies in the years to come.
- The growth in the demand for mobile business intelligence tools is also projected. Clients however, are expected to look for more case-specific products rather than just generic tools. Today, many business intelligence tools makers are continuing their research on what should be the best design so that their products would fit the mobile lifestyle of their client base. They need business solutions that should give more value to the clients. The tools that would just allow the viewing, commenting and editing of a report are a thing of the past. The new generation business intelligence tools should allow for collaboration as well as workflow approvals while being mobile.
- It is also predicted that there will be more advanced analytics that will be made available in the market. Currently, there aren't enough quantitative analysts out there in the job market that could do the complex analysis required by many companies. Thus, there would be a need and also a growth on business intelligence tools that could have more of the quantitative predictive function. This is targeted to help businessmen in the analytical and decision-making process without the need of added manpower.
- There is also an expectation that knowledge management will re-surge in importance. This will thus prod business intelligence tool vendors to invest more on technologies that will support collaboration. It would also help if the collaboration tool would include social media integration.
All of these expected future developments in it would impact the business of entrepreneurs in terms of ease of decision-making. It would also bring in convenience as the mobility and social media components are factored in. Over all, these projected developments are on the plus side for business owners.
Tuesday, November 15, 2011
What Exactly is Business Intelligence?
OLAP is that piece of the tool set that provides Dimensional Analysis, enabling huge volumes of data to be efficiently made available for exploration in a large variety of formats and arrangements.
The repository of high-volume data and the special methods for designing its storage was given the title of "Data Warehousing" (DW). Within the DW, a representation technique called "Dimensional Modeling" evolved, which is aimed at economic, context-based access (querying) of the immense tables held in the DW database.
Once the data has been captured and arranged in this way, through a process known as "Extract, Transformation and Load" (ETL), it can be passed through a further stage of processing that generates a "Cube".
The Cube, in this context is actually another highly optimized form of storage in which the Dimensionally Modelled data can be pre-aggregated and cross-mapped for efficient retrieval and presentation to the user, who can enjoy parsing data at many levels of summarization moving quickly between almost limitless varieties of analysis.
Activities such as setting up multi-dimensional charts of data summary (known as "slicing and dicing") or moving to lower levels of detail and back again to highly summarized versions (known as drill-down and drill-up), using tools to create graphical representations of the Cube data, with a great many formats from which to choose.
Employing yet other tools to perform sophisticated analyses, whereby trends and anomalies buried deep in the data may be discovered, understood and exploited (a technique called "Data Mining"). Data Mining models are created and refined to become sensitive to and resonant with the data patterns and can themselves be used to generate forecasts of future trends and movements within the tracked data. A veritable gold mine of such gems lies hidden and largely unexplored in the "exploding" mountains of data that have accumulated in companies since the price of storage came tumbling down.
It seems that IT organizations have been hanging onto data, keeping it in cold-storage, knowing that there will come a time when it will be of benefit. This is analogous to the hopefuls who upon departing this world, have their brain frozen, awaiting the emergence of technologies that can bring it back to life, perhaps with an artificial body. Business Intelligence is the technology that allows companies to unfreeze their data assets, bringing them back to a much more useful life than before. A New Era for Information Usage?
Early in the eighteenth century, inventors were making new discoveries about heat, energy and motion. There quickly evolved coal-fired, steam-driven locomotion (railways) and pumping engines (for the mines) and giant power plants for making every machine in a factory turn and churn incessantly. Spinning cotton, weaving cloth, cutting and shaping iron and then steel. The Industrial Revolution was born. Mills and factories sprung up all across the coal-rich fields of Northern England (this writer's birthplace - although a little later).
From their long heritage of back-breaking land work, people seeking to earn a regular (monetary) income flocked to grasp the many new (but equally back-breaking) factory jobs that emanated from the urban sprawl of gleaming red-bricked labyrinths, that housed these awesome machines. Industrial empires were spawning all over and wealthy (already) magnates-to-be, stepped up to invest, build and rule over them.
What did they think of Business Intelligence? Of course, it seems unlikely that the term would ever have been uttered back then but, business empires had to managed somehow. If you could see those monolithic structures and enjoy the experience of visiting them, still churning and clunking, you may notice that almost every square foot of factory space was given over to production or storage of raw materials and finished goods. No room for desks and filing cabinets and, of course, no information technology; not even a telephone!
In one corner of the giant mill, you will see a well appointed office (where the owner would be found most of the time) and one or two nearby, less auspicious areas, being the workplaces of a couple of clerks, whose job was to record all the transactions of the business. Keepers of great leather-bound volumes of hand-written fiscal matters, committed to parchment but rarely revisited. So where was the "Decision Support System"? Where were the "Executive Information Systems" and "Balanced Score Cards"?
It was all there; all that was needed in those horse-drawn days, where real business took place between the various well-heeled mill owners over a mug of coffee or a mulled ale at some local tavern, gentlemen's club or city-based mercantile gathering hall. The mill owner was kept informed of the production issues, inside his work-house, by visits from the foreman and kept his business knowledge up to scratch by his time spent over the tablecloths of his privileged meeting places. Intelligence was handled by "word of mouth". Business deals were a handshake, followed by a letter, days or weeks later.
After the initial gold rush of mechanization, little changed for a long time; at least in terms of administration methods. Only after a slow but gradual increase in the number of non-production workers and the (mostly) record-keeping tasks they performed, would another unannounced "giant leap forward" occur, to irreversibly revamp the business scene once again.
Hail, Data Processing Due to regulatory requirements, statutory accounting practices and other external demands, together with a burgeoning management's appetite for information, the ever-growing office spaces were becoming jammed with bursting-at-the- seems filing cabinets, filled with all manner of records of the company's actions, transactions and anything else that mattered. All typed-in-triplicate, carbon-copied and filed in strict order (ready to be retrieved and hand-altered or joined by an extension or superseding entry.
Hot, clattering, manufacturing machinery had ushered in the Industrial Age and hot, clattering data processing machinery would now usher in the Information Age. Tabulators, card punches, paper-tape punches and prattling line printers were among the first commercially successful data processing machines. Rapidly progressing into electronic mainframe computers, humming, or even whistling musically (but still quite hot) and requiring huge rooms for their banks of hand-threaded core-memories (as much as 8 Kilobytes per cabinet), and looms of backplane wiring to connect central processor's thousands of discreet components, soldered to hundreds of Bakelite circuit boards.
Strangely, this great revolution of number-crunching, heat-belching behemoths did little to shake up the world of business. Large corporations would quickly shell out millions for their first pride-and-joy, accompanied by the odd educational institution, here and there. However, vast swathes of less well endowed organizations held back, presumably seeing no threat of extinction as the consequence of not joining in the party for the second great era of industrialization.
Well maybe it is not so strange. The astute leaders of small to medium sized businesses (SMB's) not known for "leaping before they look", should be expected to play wall-flower, at least until the proposition looks sound, justifiable and absolutely necessary for survival. Today though, a mere sixty years on, it is hard to find any kind of business, of any shape, size or ethical standing, that does not have heavenly amounts of computing power, at every fingertip.
Bigger, faster, cheaper, more. So the years went by at the "speed of thought", everyone got onboard and computer systems became as common in the workplace as steam-pipe
leaks, machinery-induced deafness and finger blisters had become in the cotton mill.
Actually, the "Technology" part of "Information Technology" (the "T" in IT) has come an incredibly long way since the days of machines peering through holes in cardboard (which, incidentally, was first conceived of by Industrial Revolution luminary, Jacquard, the inventor of the all-important weaving loom that bears his name).
Some software of today is also astronomically more advanced than that of the mid-twentieth century. Lamentably, it is, however, the "I" in IT that has not kept pace with the advances of electronics and related cost-performance ratios.
With some exceptions, corporate use of computers has essentially become locked into the business of record keeping; frozen solid in the first great ice-age of non-progressive wheel-spinning, running faster to stand still, quagmire, where huge budgets evaporate, just trying to keep up with the avalanche of necessary upgrades and replacements.
Is that the Cavalry I hear?
Having painted a grim picture of stagnation and nil return on investment, we have paved the way for the trumpeters and knights in shining armor. So the cost of storage has come down dramatically, the data we are holding there has ballooned dramatically, now must be the time to do something with it, dramatically.
Instead of just "record keeping", let's use all this computing power and endless data in ways that can make us better at what we do. How about introducing software that performs large-scale, sophisticated analysis. How about using that sophisticated analysis to help us make better decisions. How about using improved decision making to choose a better direction to go in and better direction to improve marketing efforts, customer experience, product investment, vendor selection, volume prediction, price setting, etc.
Let's just call this whole new leap forward "Business Intelligence".
Get more intelligent about business by seeing more clearly what we have done and what has been happening around us; by predicting where trends are heading and do all this by exploiting data we already have, tools we already own and brains that have not yet been put into deep freeze.
This all sounds good. Lets get started, "as soon as the movement hits critical mass".
IS there anyone out there already using BI?
When the first great era of commercial computing began, there were early adopters and late adopters. The early adopters paid for all the R&D (as usual) and the tail-draggers paid with loss of market-share, employee job satisfaction and investor confidence. Well, not really; business and consumers were not so hurried, cost conscious or quick to change horses back then.
Today is a different story, however. Deals are canceled at contract signing, shoppers abandon their carts at the check-out, construction is halted on the first foreclosure and stock market indicators have not seen a flat line in years. Panic is the normal state-of-rest.
Businesses sink quickly and everyone is hoping that the next object that floats by will have an outboard motor, wings and booster rockets attached. One such vehicle is that broad set of capabilities currently flying under the banner of Business Intelligence.
Many companies have made a leap of faith and invested in a BI initiative. For some of those entities, valuable gains have been achieved. For others, the project has been fruitless, hard lessons learned and second attempts made from a different approach.
Compared to the early data processing efforts, today's BI ventures are light years more advanced and equally more challenging. The potential for success is there for all qualified entrants and many have proved the point. Eventually, the deployment of BI will be as ubiquitous as the first generation of applications.
Just as every organization has implemented "passive" record-keeping applications of some sort or another, there will be a time when most will also have "active", even "thinking" intelligent software that examines data, sniffs out issues, evaluates propositions, recommends actions and monitors results. If you detect a difference in those two scenarios, you are understanding the meaning of Business Intelligence.
There was a time when computers were depicted in entertainment media as futuristic and the stuff of science fiction. Now we can smile at all of that and, yes, there are differences between what novelists and screenwriters created and the more mundane, however clever, computers that support every aspect of our lives today.
Don't forget, however, that the likes of HAL, C3P0 and R2D2 are seen in laboratories where artificial intelligence and other far-out technologies are constantly making progress. In our business world, we are not looking to replace people with thinking software, but with BI we can get people thinking better (with software).
BI may not be required or mandated for every type of organization; nor is it for the faint-of-heart; nor is it for the uninitiated (i.e. Those not understanding the issues). The separate MeasureGroup™ publication "Who needs BI?" can help an organization decide if it should, or should not, be looking at a BI initiative.
A summary of Business Intelligence
The following panel contains a summary of Business Intelligence in the form of a bullet list of the most significant attributes generally being assigned to this new but not-so-new technology that is going to be recognized one day as the "second great era of computing in business".
Summary of the key aspects of Business Intelligence:
- Leveraging Data Assets to glean Insights otherwise unavailable
- Exploring Business Analytics in an almost endless variety of ways
- Gaining Competitive Advantage thru the Power of Knowledge
- Seizing Opportunities to improve Status and Profitability
- Enhancing Business Agility - First to Start - First to Finish
- Using Intelligent Questions to generate Intelligent Answers to generate Intelligent Questions...
- Enabling Proactive Management to replace Reactive Damage Control
In the early days of computers, many did not see a use for them. That was because they did not yet understand their capabilities. BI is at that same point now. BI is being enabled by a new set of software tools and technologies that are continuing to evolve.
MeasureGroup™ is an operating division of dacc limited a software house that has box-product software sales exceeding 40,000 units to date and provider of consulting services to many of the world's best known companies across Europe and the United States.
Co-founder, president and CEO, Derek A. Ashton is a career professional with more than forty years of IT experience. He was the designer of the world's first ATM for TSB Bank (now Lloyds). Also an acknowledged expert in Software Quality Engineering, Mr. Ashton has spoken to audiences at major venues on Software Process Improvement and is SEI (Software Engineering Institute) trained and certified as a CMM Assessor (Capability Maturity Model) and Software Process Designer. Derek worked directly on all of the company's Data Warehouse assignments, either in a leadership role or as the DW Architect, covering a span of over 10 years.
"Our focus today is entirely on Data Warehouse and Business Intelligence development" is the word from Mr. Ashton. "The economic climate of late dictates corporations pay much more attention to the messages hidden within the mountains of accumulated but unexploited data they possess. Their future may depend on it, so there is no time to lose. However, those companies who diligently pursue potentially massive cost savings with their BI initiative are the ones who will quickly come out on top."
"We see so many projects that drag on for years, consuming resources and not delivering. The time for agile RAD techniques, using already proven components is here and now. Everyone we speak to is desperate for a solution today but without the big-vendor price-tag that automatically promotes the effort into multi-year mayhem. This is where we have helped many companies, with one Data Mart being produced in only 5½ days."
The repository of high-volume data and the special methods for designing its storage was given the title of "Data Warehousing" (DW). Within the DW, a representation technique called "Dimensional Modeling" evolved, which is aimed at economic, context-based access (querying) of the immense tables held in the DW database.
Once the data has been captured and arranged in this way, through a process known as "Extract, Transformation and Load" (ETL), it can be passed through a further stage of processing that generates a "Cube".
The Cube, in this context is actually another highly optimized form of storage in which the Dimensionally Modelled data can be pre-aggregated and cross-mapped for efficient retrieval and presentation to the user, who can enjoy parsing data at many levels of summarization moving quickly between almost limitless varieties of analysis.
Activities such as setting up multi-dimensional charts of data summary (known as "slicing and dicing") or moving to lower levels of detail and back again to highly summarized versions (known as drill-down and drill-up), using tools to create graphical representations of the Cube data, with a great many formats from which to choose.
Employing yet other tools to perform sophisticated analyses, whereby trends and anomalies buried deep in the data may be discovered, understood and exploited (a technique called "Data Mining"). Data Mining models are created and refined to become sensitive to and resonant with the data patterns and can themselves be used to generate forecasts of future trends and movements within the tracked data. A veritable gold mine of such gems lies hidden and largely unexplored in the "exploding" mountains of data that have accumulated in companies since the price of storage came tumbling down.
It seems that IT organizations have been hanging onto data, keeping it in cold-storage, knowing that there will come a time when it will be of benefit. This is analogous to the hopefuls who upon departing this world, have their brain frozen, awaiting the emergence of technologies that can bring it back to life, perhaps with an artificial body. Business Intelligence is the technology that allows companies to unfreeze their data assets, bringing them back to a much more useful life than before. A New Era for Information Usage?
Early in the eighteenth century, inventors were making new discoveries about heat, energy and motion. There quickly evolved coal-fired, steam-driven locomotion (railways) and pumping engines (for the mines) and giant power plants for making every machine in a factory turn and churn incessantly. Spinning cotton, weaving cloth, cutting and shaping iron and then steel. The Industrial Revolution was born. Mills and factories sprung up all across the coal-rich fields of Northern England (this writer's birthplace - although a little later).
From their long heritage of back-breaking land work, people seeking to earn a regular (monetary) income flocked to grasp the many new (but equally back-breaking) factory jobs that emanated from the urban sprawl of gleaming red-bricked labyrinths, that housed these awesome machines. Industrial empires were spawning all over and wealthy (already) magnates-to-be, stepped up to invest, build and rule over them.
What did they think of Business Intelligence? Of course, it seems unlikely that the term would ever have been uttered back then but, business empires had to managed somehow. If you could see those monolithic structures and enjoy the experience of visiting them, still churning and clunking, you may notice that almost every square foot of factory space was given over to production or storage of raw materials and finished goods. No room for desks and filing cabinets and, of course, no information technology; not even a telephone!
In one corner of the giant mill, you will see a well appointed office (where the owner would be found most of the time) and one or two nearby, less auspicious areas, being the workplaces of a couple of clerks, whose job was to record all the transactions of the business. Keepers of great leather-bound volumes of hand-written fiscal matters, committed to parchment but rarely revisited. So where was the "Decision Support System"? Where were the "Executive Information Systems" and "Balanced Score Cards"?
It was all there; all that was needed in those horse-drawn days, where real business took place between the various well-heeled mill owners over a mug of coffee or a mulled ale at some local tavern, gentlemen's club or city-based mercantile gathering hall. The mill owner was kept informed of the production issues, inside his work-house, by visits from the foreman and kept his business knowledge up to scratch by his time spent over the tablecloths of his privileged meeting places. Intelligence was handled by "word of mouth". Business deals were a handshake, followed by a letter, days or weeks later.
After the initial gold rush of mechanization, little changed for a long time; at least in terms of administration methods. Only after a slow but gradual increase in the number of non-production workers and the (mostly) record-keeping tasks they performed, would another unannounced "giant leap forward" occur, to irreversibly revamp the business scene once again.
Hail, Data Processing Due to regulatory requirements, statutory accounting practices and other external demands, together with a burgeoning management's appetite for information, the ever-growing office spaces were becoming jammed with bursting-at-the- seems filing cabinets, filled with all manner of records of the company's actions, transactions and anything else that mattered. All typed-in-triplicate, carbon-copied and filed in strict order (ready to be retrieved and hand-altered or joined by an extension or superseding entry.
Hot, clattering, manufacturing machinery had ushered in the Industrial Age and hot, clattering data processing machinery would now usher in the Information Age. Tabulators, card punches, paper-tape punches and prattling line printers were among the first commercially successful data processing machines. Rapidly progressing into electronic mainframe computers, humming, or even whistling musically (but still quite hot) and requiring huge rooms for their banks of hand-threaded core-memories (as much as 8 Kilobytes per cabinet), and looms of backplane wiring to connect central processor's thousands of discreet components, soldered to hundreds of Bakelite circuit boards.
Strangely, this great revolution of number-crunching, heat-belching behemoths did little to shake up the world of business. Large corporations would quickly shell out millions for their first pride-and-joy, accompanied by the odd educational institution, here and there. However, vast swathes of less well endowed organizations held back, presumably seeing no threat of extinction as the consequence of not joining in the party for the second great era of industrialization.
Well maybe it is not so strange. The astute leaders of small to medium sized businesses (SMB's) not known for "leaping before they look", should be expected to play wall-flower, at least until the proposition looks sound, justifiable and absolutely necessary for survival. Today though, a mere sixty years on, it is hard to find any kind of business, of any shape, size or ethical standing, that does not have heavenly amounts of computing power, at every fingertip.
Bigger, faster, cheaper, more. So the years went by at the "speed of thought", everyone got onboard and computer systems became as common in the workplace as steam-pipe
leaks, machinery-induced deafness and finger blisters had become in the cotton mill.
Actually, the "Technology" part of "Information Technology" (the "T" in IT) has come an incredibly long way since the days of machines peering through holes in cardboard (which, incidentally, was first conceived of by Industrial Revolution luminary, Jacquard, the inventor of the all-important weaving loom that bears his name).
Some software of today is also astronomically more advanced than that of the mid-twentieth century. Lamentably, it is, however, the "I" in IT that has not kept pace with the advances of electronics and related cost-performance ratios.
With some exceptions, corporate use of computers has essentially become locked into the business of record keeping; frozen solid in the first great ice-age of non-progressive wheel-spinning, running faster to stand still, quagmire, where huge budgets evaporate, just trying to keep up with the avalanche of necessary upgrades and replacements.
Is that the Cavalry I hear?
Having painted a grim picture of stagnation and nil return on investment, we have paved the way for the trumpeters and knights in shining armor. So the cost of storage has come down dramatically, the data we are holding there has ballooned dramatically, now must be the time to do something with it, dramatically.
Instead of just "record keeping", let's use all this computing power and endless data in ways that can make us better at what we do. How about introducing software that performs large-scale, sophisticated analysis. How about using that sophisticated analysis to help us make better decisions. How about using improved decision making to choose a better direction to go in and better direction to improve marketing efforts, customer experience, product investment, vendor selection, volume prediction, price setting, etc.
Let's just call this whole new leap forward "Business Intelligence".
Get more intelligent about business by seeing more clearly what we have done and what has been happening around us; by predicting where trends are heading and do all this by exploiting data we already have, tools we already own and brains that have not yet been put into deep freeze.
This all sounds good. Lets get started, "as soon as the movement hits critical mass".
IS there anyone out there already using BI?
When the first great era of commercial computing began, there were early adopters and late adopters. The early adopters paid for all the R&D (as usual) and the tail-draggers paid with loss of market-share, employee job satisfaction and investor confidence. Well, not really; business and consumers were not so hurried, cost conscious or quick to change horses back then.
Today is a different story, however. Deals are canceled at contract signing, shoppers abandon their carts at the check-out, construction is halted on the first foreclosure and stock market indicators have not seen a flat line in years. Panic is the normal state-of-rest.
Businesses sink quickly and everyone is hoping that the next object that floats by will have an outboard motor, wings and booster rockets attached. One such vehicle is that broad set of capabilities currently flying under the banner of Business Intelligence.
Many companies have made a leap of faith and invested in a BI initiative. For some of those entities, valuable gains have been achieved. For others, the project has been fruitless, hard lessons learned and second attempts made from a different approach.
Compared to the early data processing efforts, today's BI ventures are light years more advanced and equally more challenging. The potential for success is there for all qualified entrants and many have proved the point. Eventually, the deployment of BI will be as ubiquitous as the first generation of applications.
Just as every organization has implemented "passive" record-keeping applications of some sort or another, there will be a time when most will also have "active", even "thinking" intelligent software that examines data, sniffs out issues, evaluates propositions, recommends actions and monitors results. If you detect a difference in those two scenarios, you are understanding the meaning of Business Intelligence.
There was a time when computers were depicted in entertainment media as futuristic and the stuff of science fiction. Now we can smile at all of that and, yes, there are differences between what novelists and screenwriters created and the more mundane, however clever, computers that support every aspect of our lives today.
Don't forget, however, that the likes of HAL, C3P0 and R2D2 are seen in laboratories where artificial intelligence and other far-out technologies are constantly making progress. In our business world, we are not looking to replace people with thinking software, but with BI we can get people thinking better (with software).
BI may not be required or mandated for every type of organization; nor is it for the faint-of-heart; nor is it for the uninitiated (i.e. Those not understanding the issues). The separate MeasureGroup™ publication "Who needs BI?" can help an organization decide if it should, or should not, be looking at a BI initiative.
A summary of Business Intelligence
The following panel contains a summary of Business Intelligence in the form of a bullet list of the most significant attributes generally being assigned to this new but not-so-new technology that is going to be recognized one day as the "second great era of computing in business".
Summary of the key aspects of Business Intelligence:
- Leveraging Data Assets to glean Insights otherwise unavailable
- Exploring Business Analytics in an almost endless variety of ways
- Gaining Competitive Advantage thru the Power of Knowledge
- Seizing Opportunities to improve Status and Profitability
- Enhancing Business Agility - First to Start - First to Finish
- Using Intelligent Questions to generate Intelligent Answers to generate Intelligent Questions...
- Enabling Proactive Management to replace Reactive Damage Control
In the early days of computers, many did not see a use for them. That was because they did not yet understand their capabilities. BI is at that same point now. BI is being enabled by a new set of software tools and technologies that are continuing to evolve.
MeasureGroup™ is an operating division of dacc limited a software house that has box-product software sales exceeding 40,000 units to date and provider of consulting services to many of the world's best known companies across Europe and the United States.
Co-founder, president and CEO, Derek A. Ashton is a career professional with more than forty years of IT experience. He was the designer of the world's first ATM for TSB Bank (now Lloyds). Also an acknowledged expert in Software Quality Engineering, Mr. Ashton has spoken to audiences at major venues on Software Process Improvement and is SEI (Software Engineering Institute) trained and certified as a CMM Assessor (Capability Maturity Model) and Software Process Designer. Derek worked directly on all of the company's Data Warehouse assignments, either in a leadership role or as the DW Architect, covering a span of over 10 years.
"Our focus today is entirely on Data Warehouse and Business Intelligence development" is the word from Mr. Ashton. "The economic climate of late dictates corporations pay much more attention to the messages hidden within the mountains of accumulated but unexploited data they possess. Their future may depend on it, so there is no time to lose. However, those companies who diligently pursue potentially massive cost savings with their BI initiative are the ones who will quickly come out on top."
"We see so many projects that drag on for years, consuming resources and not delivering. The time for agile RAD techniques, using already proven components is here and now. Everyone we speak to is desperate for a solution today but without the big-vendor price-tag that automatically promotes the effort into multi-year mayhem. This is where we have helped many companies, with one Data Mart being produced in only 5½ days."
Sunday, November 13, 2011
Implementing a Business Intelligence [BI] Vision
In my last article I shared why having a Business Intelligence Vision was important, and how to go about creating a vision to describe how business intelligence will improve performance in your organization. We now need to look at how to implement that vision. The true test of a well written vision is that it can be readily translated, or broken down into specific strategic goals. So naturally, the first step in implementing a BI vision is to create and document a BI strategy.
The implementation of a BI vision must ensure that any technology or methods employed by business intelligence projects throughout the organization fit the overall BI environment. The BI Strategy acts as a guiding roadmap for Business Intelligence project rollouts.
As with any specific strategy within an organization one must start with the overall corporate strategy. Again, this is a solid test of how well the corporate strategy is documented. If it is not explicitly clear as to what the business wants to achieve in the short and longer term, then the strategy descriptive fails. The corporate strategy must be able to be broken down into lower level business requirements, that in turn can be scrutinized by the BI Program Team to determine what BI methodology and what supporting BI technology will help deliver to that requirement.
By addressing business requirements one at a time, project iterations can tightly focus on specific business requirements of each functional area. In turn, each iteration must align with the long-term BI vision. One of the best ways of achieving this is by using a high-level, enterprise-wide BI Road Map. So let's take a quick look at each of the BI components.
The BI Strategy Plan
The BI strategy document offers insight into the BI environment, with the focus on communicating:
1. What is to be built
2. How it will be built
3. When it will be ready to meet user requirements
The BI strategy also directs BI best practices that must be adopted.
The development of the BI Strategy Plan typically takes several workshops, each session breaking the strategy down into finer detail. For instance, the first BI Strategy Plan workshop my focus at the high level, with high-level diagrams that depict the various logical parts of the organization to be assessed in terms of BI readiness and BI opportunities. It will also cover general business intelligence definitions to ensure that all communications impart the same meaning, both within the group and between the group and the business. Finally, it will cover off broad policy statements and how compliance to BI policies will be communicated and enforced.
Subsequent sessions may include representatives from key parts of the business, in particular IT and HR.
* IT - provide invaluable support in terms of how the BI goals can be integrated into the future architectural vision for the enterprise. Without a broad architectural vision, BI iterations are at risk of resulting in discrete warehouse-centric implementations rather than an enterprise-wide, informational asset.
* HR - must be consulted in terms of change management and how BI will impact personal performance and measurement. BI used at a personal level will challenge the traditional HR performance models, and as such, the BI strategy team must make themselves available early in the program to help HR understand the full power and benefits of BI and how some traditional HR performance models work against BI being accepted, and more importantly, restrict the deliverables possible from BI
The BI strategy document becomes the road map to follow as you begin implementing the BI environment, and in turn, achieve the BI vision. I will share more about the contents of a BI Strategy document in a later article.
The BI Roadmap
The BI Roadmap is a powerful tool for communicating the implementation of the BI vision, and the subsequent BI strategy. It is best kept at a high level, as with each BI project iteration, both the business and the BI project teams learn more about the power of BI, and as such the order or level of execution of following iterations is very likely to change. Further, as the business environment changes so rapidly, the needs of the business change accordingly. Hence, the relative importance of various BI projects will be in constant flux. Budgets to meet offensive opportunities can often be garnished to apply to small BI iterations. This is why implementation of BI must always be in a highly agile framework.
BI Roadmaps are best developed firstly from a business perspective, to ensure that the most important business needs are addressed first. This is then overlaid onto a BI technology roadmap, which will add an implementation difficulty element to help define the final BI implementation path. A conceptual BI Technical diagram is useful for illustrating how all the BI technology fits together, and assists with both the strategy definition and subsequent implementation planning. I will cover more about how to identify BI opportunities in a later article.
The implementation of a BI vision must ensure that any technology or methods employed by business intelligence projects throughout the organization fit the overall BI environment. The BI Strategy acts as a guiding roadmap for Business Intelligence project rollouts.
As with any specific strategy within an organization one must start with the overall corporate strategy. Again, this is a solid test of how well the corporate strategy is documented. If it is not explicitly clear as to what the business wants to achieve in the short and longer term, then the strategy descriptive fails. The corporate strategy must be able to be broken down into lower level business requirements, that in turn can be scrutinized by the BI Program Team to determine what BI methodology and what supporting BI technology will help deliver to that requirement.
By addressing business requirements one at a time, project iterations can tightly focus on specific business requirements of each functional area. In turn, each iteration must align with the long-term BI vision. One of the best ways of achieving this is by using a high-level, enterprise-wide BI Road Map. So let's take a quick look at each of the BI components.
The BI Strategy Plan
The BI strategy document offers insight into the BI environment, with the focus on communicating:
1. What is to be built
2. How it will be built
3. When it will be ready to meet user requirements
The BI strategy also directs BI best practices that must be adopted.
The development of the BI Strategy Plan typically takes several workshops, each session breaking the strategy down into finer detail. For instance, the first BI Strategy Plan workshop my focus at the high level, with high-level diagrams that depict the various logical parts of the organization to be assessed in terms of BI readiness and BI opportunities. It will also cover general business intelligence definitions to ensure that all communications impart the same meaning, both within the group and between the group and the business. Finally, it will cover off broad policy statements and how compliance to BI policies will be communicated and enforced.
Subsequent sessions may include representatives from key parts of the business, in particular IT and HR.
* IT - provide invaluable support in terms of how the BI goals can be integrated into the future architectural vision for the enterprise. Without a broad architectural vision, BI iterations are at risk of resulting in discrete warehouse-centric implementations rather than an enterprise-wide, informational asset.
* HR - must be consulted in terms of change management and how BI will impact personal performance and measurement. BI used at a personal level will challenge the traditional HR performance models, and as such, the BI strategy team must make themselves available early in the program to help HR understand the full power and benefits of BI and how some traditional HR performance models work against BI being accepted, and more importantly, restrict the deliverables possible from BI
The BI strategy document becomes the road map to follow as you begin implementing the BI environment, and in turn, achieve the BI vision. I will share more about the contents of a BI Strategy document in a later article.
The BI Roadmap
The BI Roadmap is a powerful tool for communicating the implementation of the BI vision, and the subsequent BI strategy. It is best kept at a high level, as with each BI project iteration, both the business and the BI project teams learn more about the power of BI, and as such the order or level of execution of following iterations is very likely to change. Further, as the business environment changes so rapidly, the needs of the business change accordingly. Hence, the relative importance of various BI projects will be in constant flux. Budgets to meet offensive opportunities can often be garnished to apply to small BI iterations. This is why implementation of BI must always be in a highly agile framework.
BI Roadmaps are best developed firstly from a business perspective, to ensure that the most important business needs are addressed first. This is then overlaid onto a BI technology roadmap, which will add an implementation difficulty element to help define the final BI implementation path. A conceptual BI Technical diagram is useful for illustrating how all the BI technology fits together, and assists with both the strategy definition and subsequent implementation planning. I will cover more about how to identify BI opportunities in a later article.
Friday, November 11, 2011
Business Intelligence Functions: For the Best Business Decisions
The computer based techniques that are used to dig out, spot as well as analyze any data related to business, is referred to as Business Intelligence, abbreviated as BI. These business data include the sales revenues by products and departments or by their related incomes and costs. The target of business intelligence is to help you in decision making. Although this may be used sometimes as the other name of competitive intelligence, the range of business intelligence is much more comprehensive. Rather, competitive intelligence may be held as a subpart of business intelligence. Many different processes, applications and technologies are used by business intelligence. There are, however, certain important business intelligence functions. These may be listed as data mining, benchmarking, business performance management, online analytical processing, and analytics of various types and so on.
Data mining combines different statistical methods, database management techniques as well as artificial intelligence in order to extract patterns from huge sets of data. Data mining gives great advantage of information and is considered very important for transforming data to business intelligence. It finds application in fraud detection, marketing, surveillance as well as scientific discovery.
Through benchmarking, you can compare and contrast the performance of your business as well as your business process with the best ones in the industry. You may also compare the best practices of the other different industries.
Business performance management deals with a particular set of analytic processes and management techniques to enable you to manage the performance of your organization, so that you can easily reach the goal you have set from before hand.
Through online analytical processing, abbreviated as OLAP you can readily answer any type of multidimensional analytical queries. Data mining as discussed above can be called a subpart that falls under online analytical processing as also relational reporting and business reporting. Online analytical processing can be applied in various fields. These include marketing and sales, where finds application in business reporting. It is also applied in forecasting and budgeting, management reporting, business process management, financial reporting and has up coming applications for agriculture as well.
Analytics is a very important part of business and it is a very broad category as well. It applies computer technology, statistics as well as operations research, in order to find a solution to industrial as well as business problems. Analytics includes Predictive analytics as well, which is also a function of business. It includes within, a huge variety of statistical techniques, gaming theories as well as data mining techniques. It predicts future events, by analyzing different historical and current facts.
Data mining combines different statistical methods, database management techniques as well as artificial intelligence in order to extract patterns from huge sets of data. Data mining gives great advantage of information and is considered very important for transforming data to business intelligence. It finds application in fraud detection, marketing, surveillance as well as scientific discovery.
Through benchmarking, you can compare and contrast the performance of your business as well as your business process with the best ones in the industry. You may also compare the best practices of the other different industries.
Business performance management deals with a particular set of analytic processes and management techniques to enable you to manage the performance of your organization, so that you can easily reach the goal you have set from before hand.
Through online analytical processing, abbreviated as OLAP you can readily answer any type of multidimensional analytical queries. Data mining as discussed above can be called a subpart that falls under online analytical processing as also relational reporting and business reporting. Online analytical processing can be applied in various fields. These include marketing and sales, where finds application in business reporting. It is also applied in forecasting and budgeting, management reporting, business process management, financial reporting and has up coming applications for agriculture as well.
Analytics is a very important part of business and it is a very broad category as well. It applies computer technology, statistics as well as operations research, in order to find a solution to industrial as well as business problems. Analytics includes Predictive analytics as well, which is also a function of business. It includes within, a huge variety of statistical techniques, gaming theories as well as data mining techniques. It predicts future events, by analyzing different historical and current facts.
Wednesday, November 9, 2011
Naked Business Intelligence
Naked Business Intelligence XXX - only for experts
There are many types of business intelligence solutions in company Decision Support Systems. They've been used for enhancing business decisions, strategic decisions and better leadership.Some examples of BI solutions are campaign management, customer segmentation, churn prediction, material management, dashboards, balance scorecards, economic value add, activity based costing, product calculators, contract management,different data mining solutions and many more.Business has variety of needs that need to be covered with different solutions and specific requests urge for specific solutions.That is the reason for so many different BI variations.
Fact is that today there is no one stop shop solution, one single solution for Business intelligence. In other words there is no group of BI solutions that can cover all decision support systems information needs. Like in many other fields of life there are no single platforms vendors solutions for all types of industry specifics.
Furthermore BI software variations van be grouped according to functionalities like: data mining, business performance management (BPM), specialized BI modules and "standard" BI.There is a difference between Business Performance Management and all other BI solutions is in field of usage, BPM is designed for finance and management reporting and other BI for all non financial customers. Let's call them business customers.
Standard BI is simple business intelligence without mixture with finance and without applied specialized functionalities and coding according to specialized fields of usage. It's prime role is to deliver data from production systems properly filtered and formatted. User combines from prepared reports or cubes any ad-hoc query or standard report in no time. Only limit is methodology of data extraction, data quality and process-reporting transparency.That's it, nothing more like graphs, semaphores, comparisons, dashboards, comments and etc. Standard BI provides pure data extraction and data presentation and that is the reason why we like to call it NAKED Business Intelligence.It is so simple and it is so powerful for data presentation and analysis.
There are many types of business intelligence solutions in company Decision Support Systems. They've been used for enhancing business decisions, strategic decisions and better leadership.Some examples of BI solutions are campaign management, customer segmentation, churn prediction, material management, dashboards, balance scorecards, economic value add, activity based costing, product calculators, contract management,different data mining solutions and many more.Business has variety of needs that need to be covered with different solutions and specific requests urge for specific solutions.That is the reason for so many different BI variations.
Fact is that today there is no one stop shop solution, one single solution for Business intelligence. In other words there is no group of BI solutions that can cover all decision support systems information needs. Like in many other fields of life there are no single platforms vendors solutions for all types of industry specifics.
Furthermore BI software variations van be grouped according to functionalities like: data mining, business performance management (BPM), specialized BI modules and "standard" BI.There is a difference between Business Performance Management and all other BI solutions is in field of usage, BPM is designed for finance and management reporting and other BI for all non financial customers. Let's call them business customers.
Standard BI is simple business intelligence without mixture with finance and without applied specialized functionalities and coding according to specialized fields of usage. It's prime role is to deliver data from production systems properly filtered and formatted. User combines from prepared reports or cubes any ad-hoc query or standard report in no time. Only limit is methodology of data extraction, data quality and process-reporting transparency.That's it, nothing more like graphs, semaphores, comparisons, dashboards, comments and etc. Standard BI provides pure data extraction and data presentation and that is the reason why we like to call it NAKED Business Intelligence.It is so simple and it is so powerful for data presentation and analysis.
Saturday, November 5, 2011
Business Intelligence Tools - How Can the Organizations Gain Benefit From This Software?
In today's competitive business world, many companies are required to collect a tremendous amount of data from their daily business operations. In order to keep track with all the information in a proper manner, these companies need to apply a wide range of software programs like Excel, Access and other database applications for their various departments. Honestly speaking, utilizing multiple software programs is not a good method. It is difficult to retrieve the required information fast. At the same time, the users also find it troublesome to perform analysis of data when the data is stored using different software programs. In order to overcome these problems, the Business Intelligence Tools have been created.
Business Intelligence Tools are new to many people. These tools are a type of application software which is specially designed to gather, store, access and analyze corporate data in an effective manner. In the point of view of many IT experts, this particular software plays a key role in the strategic planning process of the corporations because it allows multiple ways of looking at the complex data. It can be widely used in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, inventory and distribution analysis, and many more.
This software sounds helpful. Is it really true? Let's read on.
Basically, there are different types of Business Intelligence Tools in the market. By knowing the features of different types of tools, you will be able to make use of this software program at an optimum level.
• Query tools
These tools are very powerful as they have the capability to extract, sort, summarize and present data that is extremely important in a very quick manner. They allow the users to ask questions about the data. No matter how complex the data is, the decision makers of the business organizations are able to make fast decision with these tools.
• Multidimensional analysis tools
They are also known as Online Analytical Processing. These tools allow the users to view the same data from different aspects.
• Data mining tools
These tools are commonly used for marketing, surveillance and fraud detection. They are automated to search data and seek out ways that the data correlates to other data. They help to create key patterns which enable the top management to operate and change the business if required.
• Spreadsheets
It plays an important role in crunching the financial data and summarizing key accounting numbers. The users will be able to create reports fast. At the same time, if there is any modification of the data, the spreadsheets are able to recalculate in an efficient manner.
• Digital Dashboards
These tools are very popular among the key decision makers because all the performance measures, key trends and reports can presented clearly through visual display.
For people who are currently looking for this particular software, I would recommend you to look for the reputable providers like IBM, Microsoft, Oracle, SAP and SAS Global. If cost is your main concern, you are advised to compare the prices of different tool providers before making your decision. Since different users have different needs, you are reminded to find out the features of different tools and evaluate them carefully. Make sure the tools you choose are able to meet your organization's needs.
Business Intelligence Tools are new to many people. These tools are a type of application software which is specially designed to gather, store, access and analyze corporate data in an effective manner. In the point of view of many IT experts, this particular software plays a key role in the strategic planning process of the corporations because it allows multiple ways of looking at the complex data. It can be widely used in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, inventory and distribution analysis, and many more.
This software sounds helpful. Is it really true? Let's read on.
Basically, there are different types of Business Intelligence Tools in the market. By knowing the features of different types of tools, you will be able to make use of this software program at an optimum level.
• Query tools
These tools are very powerful as they have the capability to extract, sort, summarize and present data that is extremely important in a very quick manner. They allow the users to ask questions about the data. No matter how complex the data is, the decision makers of the business organizations are able to make fast decision with these tools.
• Multidimensional analysis tools
They are also known as Online Analytical Processing. These tools allow the users to view the same data from different aspects.
• Data mining tools
These tools are commonly used for marketing, surveillance and fraud detection. They are automated to search data and seek out ways that the data correlates to other data. They help to create key patterns which enable the top management to operate and change the business if required.
• Spreadsheets
It plays an important role in crunching the financial data and summarizing key accounting numbers. The users will be able to create reports fast. At the same time, if there is any modification of the data, the spreadsheets are able to recalculate in an efficient manner.
• Digital Dashboards
These tools are very popular among the key decision makers because all the performance measures, key trends and reports can presented clearly through visual display.
For people who are currently looking for this particular software, I would recommend you to look for the reputable providers like IBM, Microsoft, Oracle, SAP and SAS Global. If cost is your main concern, you are advised to compare the prices of different tool providers before making your decision. Since different users have different needs, you are reminded to find out the features of different tools and evaluate them carefully. Make sure the tools you choose are able to meet your organization's needs.
Thursday, November 3, 2011
Intelligence Careers - With SAP Business Intelligence (BI) in Federal Government Contracts
SAP Software Government solutions are being adopted by many federal government agencies and now becoming mainstream in federal government environment. The logical next step is to build business intelligence capability to analyze the data.
About the SAP BI tool: It is a reporting system which seamlessly connects with the SAP Software to extract the data so the user can report on the data with user friendly front end tools. SAP BI can also connect to other external data sources. The main advantage of connecting to SAP Software is that SAP Software has inbuilt extractors in the system. The extractors can be leveraged to quickly deploy the SAP BI System. These sap extractors are pre built they have all the business rules implemented.
Intelligence Career opportunities in new Implementations:
Once the SAP Software is stable, clients want to install SAP Business intelligence. This is because running reports in SAP Software directly degrades the SAP System performance. SAP Business intelligence is part of all the SAP ECC systems. For small clients they can run SAP BI and SAP Business Software in the same system. This way they do not have spend money on expensive software
Intelligence Career opportunities in upgrades and Business objects:
With the purchase of the business objects software SAP is pushing all the clients to migrate to the new SAP Business Objects front end. Then means there will be lot of work with recreating the reports, testing and documentation. If consultants has reporting experience they can comfortably assimilate into the SAP Business object consulting market
Intelligence Career:
If you have any kind of business warehouse experience then that can be leverage to get into consulting career. The basic concept of creating the reporting is same. You can upgrade / tweak your skills to adapt to the new environment. Most of the federal government Clearance Careers requires US Citizenship and clean personal record. You have to be ready to open up your personal life. The investigations will get into your personal finances and relationships with your family and friends. This can sometimes be very can intensive.
Tip:
Do not ignore the job just because it is requiring secret clearance. That means they prefer to have professional who have previous clearance. But that does not mean they will ignore consultants who have good experience and skills. So apply to any job which fits your skill set. Eventually you will have match and get into the job.
The Benefit:
Most of the Federal Secret Clearance jobs are high paid and also longterm. If you do not mind the scrutiny then it definitely a good option to venture into Intelligence careers with SAP Software
Specializing in training NON-IT people for IT Jobs. There is tremendous opportunity for people with business skills. Most of the Business application software require business and functional knowledge. I provide SAP Security and Audit compliance training. The core modules we cover are SAP Security, SAP GRC audit with risk analysis and remediation tool, SAP audit GRC Superuser prevailage management, SAP audit GRC compliant user provisioning tool, SAP Business intelligence security, SAP business warehouse security, SAP Audit Compliance and sap automation. In addition to training we also help the students with job placement. We help with resume preparation, mock interviews and job support.
About the SAP BI tool: It is a reporting system which seamlessly connects with the SAP Software to extract the data so the user can report on the data with user friendly front end tools. SAP BI can also connect to other external data sources. The main advantage of connecting to SAP Software is that SAP Software has inbuilt extractors in the system. The extractors can be leveraged to quickly deploy the SAP BI System. These sap extractors are pre built they have all the business rules implemented.
Intelligence Career opportunities in new Implementations:
Once the SAP Software is stable, clients want to install SAP Business intelligence. This is because running reports in SAP Software directly degrades the SAP System performance. SAP Business intelligence is part of all the SAP ECC systems. For small clients they can run SAP BI and SAP Business Software in the same system. This way they do not have spend money on expensive software
Intelligence Career opportunities in upgrades and Business objects:
With the purchase of the business objects software SAP is pushing all the clients to migrate to the new SAP Business Objects front end. Then means there will be lot of work with recreating the reports, testing and documentation. If consultants has reporting experience they can comfortably assimilate into the SAP Business object consulting market
Intelligence Career:
If you have any kind of business warehouse experience then that can be leverage to get into consulting career. The basic concept of creating the reporting is same. You can upgrade / tweak your skills to adapt to the new environment. Most of the federal government Clearance Careers requires US Citizenship and clean personal record. You have to be ready to open up your personal life. The investigations will get into your personal finances and relationships with your family and friends. This can sometimes be very can intensive.
Tip:
Do not ignore the job just because it is requiring secret clearance. That means they prefer to have professional who have previous clearance. But that does not mean they will ignore consultants who have good experience and skills. So apply to any job which fits your skill set. Eventually you will have match and get into the job.
The Benefit:
Most of the Federal Secret Clearance jobs are high paid and also longterm. If you do not mind the scrutiny then it definitely a good option to venture into Intelligence careers with SAP Software
Specializing in training NON-IT people for IT Jobs. There is tremendous opportunity for people with business skills. Most of the Business application software require business and functional knowledge. I provide SAP Security and Audit compliance training. The core modules we cover are SAP Security, SAP GRC audit with risk analysis and remediation tool, SAP audit GRC Superuser prevailage management, SAP audit GRC compliant user provisioning tool, SAP Business intelligence security, SAP business warehouse security, SAP Audit Compliance and sap automation. In addition to training we also help the students with job placement. We help with resume preparation, mock interviews and job support.
Tuesday, November 1, 2011
Quick Guide to Implementing Business Intelligence, Data Warehousing & BPM
Definitions and Overview
Business Performance Management (BPM) establishes a framework to improve business performance by measuring key business characteristics which can be used to feedback into the decision process and guide operations in an attempt to improve strategic organisational performance. Other popular terms for this include; Enterprise PM (EPM), Corporate PM (CPM) Enterprise Information Systems (EIS), Decision Support Systems (DSS), Management Information Systems (MIS).
BPM: Cycle of setting objectives, monitoring performance and feeding back to new objectives.
Business Intelligence (BI) can be defined as the set of tools which allows end-users easy access to relevant information and the facility to analyse this to aid decision making. More widely the 'intelligence' is the insight which is derived from this analysis (eg. trends and correlations).
BI: Tools to Access & Analyse Data
Key Performance Indicators (KPIs) are strategically aligned corporate measures that are used to monitor, predict and anticipate the performance of the organisation. They form the basis of any the BPM solution and in an ideal world it should be possible to relate strategic KPIs to actual operational performance within the BI application.
KPIs provide a quick indication on the health of the organisation and guide management to the operational areas affecting performance.
In many companies analysis of data is complicated by the fact that data is fragmented within the business. This causes problems of duplication, inconsistent definitions, inconsistency, inaccuracy and wasted effort.
Silos of Data: Fragmented, Departmental Data Stores, often aligned with specific business areas.
Data Warehousing (DWH) is often the first step towards BI. A Data Warehouse is a centralised pool of data structured to facilitate access and analysis.
DWH: Centralised/Consolidated Data Store
The DWH will be populated from various sources (heterogeneous) using an ETL (Extract, Transform & Load) or data integration tool. This update may be done in regular periodic batches, as a one off load or even synchronised with the source data (real time).
ETL: The process of extracting data from a source system, transforming (or validating) it and loading it into a structured database.
A reporting (or BI) layer can then be used to analyse the consolidated data and create dashboards and user defined reports. A modelling layer can be used to integrate budgets and forecasting.
As these solutions get more complex, the definitions of the systems and what they are doing becomes more important. This is known as metadata and represents the data defining the actual data and its manipulation. Each part of the system has its own metadata defining what it is doing. Good management & use of metadata reduces development time, makes ongoing maintenance simpler and provides users with information about the source of the data, increasing their trust and understanding of it.
Metadata: Data about data, describing how and where it is being used, where it came from and what changes have been made to it.
Commercial Justifications
There is clear commercial justification to improve the quality of information used for decision making. A survey conducted by IDC found that the mean payback of BI implementation was 1.6 years and that 54% of businesses had a 5 year ROI of >101% and 20% had ROI > 1000%.
ROI on BI > 1000% from 20% of organisations
There are now also regulatory requirements to be considered. Sarbanes-Oxley requires that US listed companies disclose and monitor key risks and relevant performance indicators - both financial and non financial in their annual reports. A robust reporting infrastructure is essential for achieving this.
SarbOx requires disclosure of financial & non-financial KPIs
Poor data quality is a common barrier to accurate reporting and informed decision making. A good data quality strategy, encompassing non system issues such as user training and procedures can have a large impact. Consolidating data into a DWH can help ensure consistency and correct poor data, but it also provides an accurate measure of data quality allowing it to be managed more pro-actively.
Data Quality is vital and a formal data quality strategy is essential to continually manage and improve it.
Recent research (PMP Research) asked a broad cross section of organisations their opinion of their data quality before and after a DWH implementation.
- "Don't know" responses decreased from 17% to 7%
- "Bad" or "Very Bad" decreased from 40% to 9%
- Satisfactory (or better) increased from 43% to 84%
DWH implementations improve Data Quality.
Tools Market Overview
At present BI is seen as a significant IT growth area and as such everyone is trying to get onto the BI bandwagon:
ERP tools have BI solutions e.g SAP BW, Oracle Apps
CRM tools are doing it: Siebel Analytics,
ETL vendors are adding BI capabilities: Informatica
BI vendors are adding ETL tools: Business Objects (BO) Data Integrator (DI), Cognos Decision Stream
Database vendors are extending their BI & ETL tools:
Oracle: Oracle Warehouse Builder, EPM
Microsoft: SQL 2005, Integration Services, Reporting Services, Analytical Services
Improved Tools
Like all maturing markets, consolidation has taken place whereby fewer suppliers now cover more functionality. This is good for customers as more standardisation, better use of metadata and improved functionality is now easily available. BI tools today can now satisfy the most demanding customer's requirements for information.
Thinking and tools have moved on - we can now build rapid, business focussed solutions in small chunks - allowing business to see data, store knowledge, learn capabilities of new tools and refine their requirements during the project! Gone are the days of the massive data warehousing project, which was obsolete before it was completed.
A typical DWH project should provide usable results within 3 - 6 Months.
Advice & Best Practice
Initial Phase
Successful BI projects will never finish. It should perpetually evolve to meet the changing needs of the business. So first 'wins' need to come quickly and tools and techniques need to be flexible, quick to develop and quick to deploy.
Experience is Essential
Often we have been brought in to correct failed projects and it is frightening how many basic mistakes are made through inexperience. A data warehouse is fundamentally different to your operational systems and getting the initial design and infrastructure correct is crucial to satisfying business demands.
Keep Internal Control
We believe that BI is too close to the business and changes too fast to outsource. Expertise is required in the initial stages, to ensure that a solid infrastructure is in place (and use of the best tools and methods.) If sufficient experience is not available internally external resource can be useful in the initial stages but this MUST include skills transfer to internal resources. The DWH can then grow and evolve (with internal resourcing) to meet the changing needs of the business.
Ensure Management and User Buy In
It may sound obvious but internal knowledge and support is essential for the success of a DWH, yet 'Reporting' is often given a low priority and can easily be neglected unless it is supported at a senior business level. It is common to find that there is a limited knowledge of user requirements. It is also true that requirements will change over time both in response to changing business needs and to the findings/outcomes of the DWH implementation and use of new tools.
Strong Project Management
The complex and iterative nature of a data warehouse project requires strong project management. The relatively un-quantifiable risk around data quality needs managing along with changing user requirements. Plan for change and allow extra budget for the unexpected. Using rapid application development techniques (RAD) mitigates some of the risks by exposing them early in the project with the use of proto-types.
Educating the End Users
Do not under estimate the importance of training when implementing a new BI/ DWH solution. Trained users are 60% more successful in realising the benefits of BI than untrained users. But this training needs to consider specific data analysis techniques as well as how to use the BI tools. In the words of Gartner, "it is more critical to train users on how to analyse the data." Gartner goes on to say "... that focusing only on BI tool training can triple the workload of the IT help desk and result in user disillusionment. A user who is trained on the BI tool but does not know how to use it in the context of his or her BI/DWH environment will not be able to get the analytical results he or she needs...". Hence bespoke user training on your BI system and data is essential.
Careful planning of the training needs and making the best use of the different training mediums now available can overcome this issue. Look for training options such as: Structured classroom (on or off site), web based e-learning (CBT), on the job training & skills transfer, bespoke training around your solution & data.
Technical Overview
Information Portal: This allows users to manage & access reports and other information via a corporate web portal. As users create & demand more reports the ability to easily find, manage & distribute them is becoming more important.
Collaboration: The ability for the Information Portal to support communication between relevant people centred around the information in the portal. This could be discussion threads attached to reports or workflow around strategic goal performance.
Guided Analysis: The system guides users where to look next during data analysis. Taking knowledge from people's heads and placing it in the BI system.
Security: Access to system functionality and data (both rows and columns) can be controlled down to user level and based on your network logon.
Dashboards & Scorecards:
Providing management with a high level, graphical view of their business performance (KPIs) with easy drill down to the underlying operational detail.
Ad-hoc Reporting and Data Analysis: End users can easily extract data, analyse it (slice, dice & drill) and formally present it in reports & distribute them.
Formatted/ Standard Reports: Pre-defined, pixel perfect, often complex reports created by IT. The power of end user reporting tools and data warehousing is now making this type of report writing less technical and more business focussed.
Tight MS Office integration: More users depend on MS Office software, therefore the BI tool needs to seamlessly link into these tools.
Write Back: The BI portal should provide access to write back to the database to maintain: reference data, targets, forecasts, workflow.
Business Modelling/ Alerting: around centrally maintained data with pre-defined, end user maintained, business rules.
Real Time: As the source data changes it is instantly passed through to the user. Often via message queues.
Near Real Time: Source data changes are batched up and sent through on a short time period, say every few minutes - this requires special ETL techniques.
Batch Processing: Source Data is captured in bulk, say overnight, whilst the BI system is offline.
Relational Database Vs OLAP (cubes, slice & dice, pivot)
This is a complex argument, but put simply most things performed in an OLAP cube can be achieved in the relational world but may be slower both to execute and develop. As a rule of thumb, if you already work in a relational database environment, OLAP should only be necessary where analysis performance is an issue or you require specialist functionality, such as budgeting, forecasting or 'what if' modelling. The leading BI tools seamlessly provide access to data in either relational or OLAP form, making this primarily a technology decision rather than a business one.
Top Down or Bottom Up Approach?
The top down approach focuses on strategic goals and the business processes and organisational structure to support them. This may produce the ideal company processes but existing systems are unlikely to support them or provide the data necessary to measure them. This can lead to a strategy that is never adopted because there is no physical delivery and strategic goals cannot be measured.
The bottom up approach takes the existing systems and data and presents it to the business for them to measure & analyse. This may not produce the best strategic information due to the limited data available and data quality.
We recommend a compromise of both approaches: Build the pragmatic bottom up solution as a means to get accurate measures of the business and a better understanding of current processes, whilst performing a top down analysis to understand what the business needs strategically. The gap analysis of what can be achieved today and what is desired strategically will then provide the future direction for the solution and if the solution has been designed with change in mind, this should be relatively straight forward, building upon the system foundations already in place.
Advanced Business Intelligence
The following describes some advanced BI requirements that some organisations may want to consider: Delivering an integrated BPM solution which has business rules and workflow built in allowing the system to quickly guide the decision maker to the relevant information.
Collaboration and Guided Analysis to help manage the action required as a result of the information obtained.
More user friendly Data Mining and Predictive Analytics, where the system finds correlations between un-related data sets in order to find the 'golden nugget' of information.
More integration of BI information into the Front Office Systems e.g. a gold rated customer gets VIP treatment when they call in, data profiling to suggest this customer may churn, hence offer them an incentive to stay.
Increased usage of Real Time data.
End to end Data Lineage automatically captured by the tools. Better metadata management of the systems will mean that users can easily see where the data came from and what transformations it has undergone, improving the trust in the data & reports. Systems will also be self documenting providing users with more help information and simplifying ongoing maintenance.
Integrated, real time Data Quality Management as a means to measure accuracy of operational process performance. This would provide cross system validation, and verify business process performance by monitoring data accuracy, leading to better and more dynamic process modelling, business process re-engineering and hence efficiency gains.
Packaged Analytical Applications like finance systems in the 80's and packaged ERP (Enterprise Requirement Planning) in the 90's. Packaged BI may become the standard for this decade. Why build your own data warehouse and suite of reports and dashboards from scratch when your business is similar to many others? Buy packaged elements and use rapid deployment templates and tools to configure them to meet your precise needs. This rapid deployment capability then supports you as your business evolves.
BI for the masses: As information becomes more critical to manage operational efficiencies, more people need access to that information. Now the BI tools can technically and cost effectively provide more people with access to information, BI for the masses is now reality and can provide significant improvement to a business. The increased presence of Microsoft in the BI space will also increase usage of BI and make it more attractive. BusinessObjects' acquisition of Crystal and recent release of XI will also extend BI to more people, in and outside the organisation - now everyone can be given secure access to information!
Conclusion
The potential benefits from a BI/DWH implementation are huge but far too many companies fail to realise these through: lack of experience, poor design, poor selection and use of tools, poor management of data quality, poor or no project management, limited understanding of the importance of metadata, no realisation that if it is successful it will inevitably evolve and grow, limited awareness of the importance of training..... with all these areas to consider using a specialist consultancy such as IT Performs makes considerable sense.
Business Performance Management (BPM) establishes a framework to improve business performance by measuring key business characteristics which can be used to feedback into the decision process and guide operations in an attempt to improve strategic organisational performance. Other popular terms for this include; Enterprise PM (EPM), Corporate PM (CPM) Enterprise Information Systems (EIS), Decision Support Systems (DSS), Management Information Systems (MIS).
BPM: Cycle of setting objectives, monitoring performance and feeding back to new objectives.
Business Intelligence (BI) can be defined as the set of tools which allows end-users easy access to relevant information and the facility to analyse this to aid decision making. More widely the 'intelligence' is the insight which is derived from this analysis (eg. trends and correlations).
BI: Tools to Access & Analyse Data
Key Performance Indicators (KPIs) are strategically aligned corporate measures that are used to monitor, predict and anticipate the performance of the organisation. They form the basis of any the BPM solution and in an ideal world it should be possible to relate strategic KPIs to actual operational performance within the BI application.
KPIs provide a quick indication on the health of the organisation and guide management to the operational areas affecting performance.
In many companies analysis of data is complicated by the fact that data is fragmented within the business. This causes problems of duplication, inconsistent definitions, inconsistency, inaccuracy and wasted effort.
Silos of Data: Fragmented, Departmental Data Stores, often aligned with specific business areas.
Data Warehousing (DWH) is often the first step towards BI. A Data Warehouse is a centralised pool of data structured to facilitate access and analysis.
DWH: Centralised/Consolidated Data Store
The DWH will be populated from various sources (heterogeneous) using an ETL (Extract, Transform & Load) or data integration tool. This update may be done in regular periodic batches, as a one off load or even synchronised with the source data (real time).
ETL: The process of extracting data from a source system, transforming (or validating) it and loading it into a structured database.
A reporting (or BI) layer can then be used to analyse the consolidated data and create dashboards and user defined reports. A modelling layer can be used to integrate budgets and forecasting.
As these solutions get more complex, the definitions of the systems and what they are doing becomes more important. This is known as metadata and represents the data defining the actual data and its manipulation. Each part of the system has its own metadata defining what it is doing. Good management & use of metadata reduces development time, makes ongoing maintenance simpler and provides users with information about the source of the data, increasing their trust and understanding of it.
Metadata: Data about data, describing how and where it is being used, where it came from and what changes have been made to it.
Commercial Justifications
There is clear commercial justification to improve the quality of information used for decision making. A survey conducted by IDC found that the mean payback of BI implementation was 1.6 years and that 54% of businesses had a 5 year ROI of >101% and 20% had ROI > 1000%.
ROI on BI > 1000% from 20% of organisations
There are now also regulatory requirements to be considered. Sarbanes-Oxley requires that US listed companies disclose and monitor key risks and relevant performance indicators - both financial and non financial in their annual reports. A robust reporting infrastructure is essential for achieving this.
SarbOx requires disclosure of financial & non-financial KPIs
Poor data quality is a common barrier to accurate reporting and informed decision making. A good data quality strategy, encompassing non system issues such as user training and procedures can have a large impact. Consolidating data into a DWH can help ensure consistency and correct poor data, but it also provides an accurate measure of data quality allowing it to be managed more pro-actively.
Data Quality is vital and a formal data quality strategy is essential to continually manage and improve it.
Recent research (PMP Research) asked a broad cross section of organisations their opinion of their data quality before and after a DWH implementation.
- "Don't know" responses decreased from 17% to 7%
- "Bad" or "Very Bad" decreased from 40% to 9%
- Satisfactory (or better) increased from 43% to 84%
DWH implementations improve Data Quality.
Tools Market Overview
At present BI is seen as a significant IT growth area and as such everyone is trying to get onto the BI bandwagon:
ERP tools have BI solutions e.g SAP BW, Oracle Apps
CRM tools are doing it: Siebel Analytics,
ETL vendors are adding BI capabilities: Informatica
BI vendors are adding ETL tools: Business Objects (BO) Data Integrator (DI), Cognos Decision Stream
Database vendors are extending their BI & ETL tools:
Oracle: Oracle Warehouse Builder, EPM
Microsoft: SQL 2005, Integration Services, Reporting Services, Analytical Services
Improved Tools
Like all maturing markets, consolidation has taken place whereby fewer suppliers now cover more functionality. This is good for customers as more standardisation, better use of metadata and improved functionality is now easily available. BI tools today can now satisfy the most demanding customer's requirements for information.
Thinking and tools have moved on - we can now build rapid, business focussed solutions in small chunks - allowing business to see data, store knowledge, learn capabilities of new tools and refine their requirements during the project! Gone are the days of the massive data warehousing project, which was obsolete before it was completed.
A typical DWH project should provide usable results within 3 - 6 Months.
Advice & Best Practice
Initial Phase
Successful BI projects will never finish. It should perpetually evolve to meet the changing needs of the business. So first 'wins' need to come quickly and tools and techniques need to be flexible, quick to develop and quick to deploy.
Experience is Essential
Often we have been brought in to correct failed projects and it is frightening how many basic mistakes are made through inexperience. A data warehouse is fundamentally different to your operational systems and getting the initial design and infrastructure correct is crucial to satisfying business demands.
Keep Internal Control
We believe that BI is too close to the business and changes too fast to outsource. Expertise is required in the initial stages, to ensure that a solid infrastructure is in place (and use of the best tools and methods.) If sufficient experience is not available internally external resource can be useful in the initial stages but this MUST include skills transfer to internal resources. The DWH can then grow and evolve (with internal resourcing) to meet the changing needs of the business.
Ensure Management and User Buy In
It may sound obvious but internal knowledge and support is essential for the success of a DWH, yet 'Reporting' is often given a low priority and can easily be neglected unless it is supported at a senior business level. It is common to find that there is a limited knowledge of user requirements. It is also true that requirements will change over time both in response to changing business needs and to the findings/outcomes of the DWH implementation and use of new tools.
Strong Project Management
The complex and iterative nature of a data warehouse project requires strong project management. The relatively un-quantifiable risk around data quality needs managing along with changing user requirements. Plan for change and allow extra budget for the unexpected. Using rapid application development techniques (RAD) mitigates some of the risks by exposing them early in the project with the use of proto-types.
Educating the End Users
Do not under estimate the importance of training when implementing a new BI/ DWH solution. Trained users are 60% more successful in realising the benefits of BI than untrained users. But this training needs to consider specific data analysis techniques as well as how to use the BI tools. In the words of Gartner, "it is more critical to train users on how to analyse the data." Gartner goes on to say "... that focusing only on BI tool training can triple the workload of the IT help desk and result in user disillusionment. A user who is trained on the BI tool but does not know how to use it in the context of his or her BI/DWH environment will not be able to get the analytical results he or she needs...". Hence bespoke user training on your BI system and data is essential.
Careful planning of the training needs and making the best use of the different training mediums now available can overcome this issue. Look for training options such as: Structured classroom (on or off site), web based e-learning (CBT), on the job training & skills transfer, bespoke training around your solution & data.
Technical Overview
Information Portal: This allows users to manage & access reports and other information via a corporate web portal. As users create & demand more reports the ability to easily find, manage & distribute them is becoming more important.
Collaboration: The ability for the Information Portal to support communication between relevant people centred around the information in the portal. This could be discussion threads attached to reports or workflow around strategic goal performance.
Guided Analysis: The system guides users where to look next during data analysis. Taking knowledge from people's heads and placing it in the BI system.
Security: Access to system functionality and data (both rows and columns) can be controlled down to user level and based on your network logon.
Dashboards & Scorecards:
Providing management with a high level, graphical view of their business performance (KPIs) with easy drill down to the underlying operational detail.
Ad-hoc Reporting and Data Analysis: End users can easily extract data, analyse it (slice, dice & drill) and formally present it in reports & distribute them.
Formatted/ Standard Reports: Pre-defined, pixel perfect, often complex reports created by IT. The power of end user reporting tools and data warehousing is now making this type of report writing less technical and more business focussed.
Tight MS Office integration: More users depend on MS Office software, therefore the BI tool needs to seamlessly link into these tools.
Write Back: The BI portal should provide access to write back to the database to maintain: reference data, targets, forecasts, workflow.
Business Modelling/ Alerting: around centrally maintained data with pre-defined, end user maintained, business rules.
Real Time: As the source data changes it is instantly passed through to the user. Often via message queues.
Near Real Time: Source data changes are batched up and sent through on a short time period, say every few minutes - this requires special ETL techniques.
Batch Processing: Source Data is captured in bulk, say overnight, whilst the BI system is offline.
Relational Database Vs OLAP (cubes, slice & dice, pivot)
This is a complex argument, but put simply most things performed in an OLAP cube can be achieved in the relational world but may be slower both to execute and develop. As a rule of thumb, if you already work in a relational database environment, OLAP should only be necessary where analysis performance is an issue or you require specialist functionality, such as budgeting, forecasting or 'what if' modelling. The leading BI tools seamlessly provide access to data in either relational or OLAP form, making this primarily a technology decision rather than a business one.
Top Down or Bottom Up Approach?
The top down approach focuses on strategic goals and the business processes and organisational structure to support them. This may produce the ideal company processes but existing systems are unlikely to support them or provide the data necessary to measure them. This can lead to a strategy that is never adopted because there is no physical delivery and strategic goals cannot be measured.
The bottom up approach takes the existing systems and data and presents it to the business for them to measure & analyse. This may not produce the best strategic information due to the limited data available and data quality.
We recommend a compromise of both approaches: Build the pragmatic bottom up solution as a means to get accurate measures of the business and a better understanding of current processes, whilst performing a top down analysis to understand what the business needs strategically. The gap analysis of what can be achieved today and what is desired strategically will then provide the future direction for the solution and if the solution has been designed with change in mind, this should be relatively straight forward, building upon the system foundations already in place.
Advanced Business Intelligence
The following describes some advanced BI requirements that some organisations may want to consider: Delivering an integrated BPM solution which has business rules and workflow built in allowing the system to quickly guide the decision maker to the relevant information.
Collaboration and Guided Analysis to help manage the action required as a result of the information obtained.
More user friendly Data Mining and Predictive Analytics, where the system finds correlations between un-related data sets in order to find the 'golden nugget' of information.
More integration of BI information into the Front Office Systems e.g. a gold rated customer gets VIP treatment when they call in, data profiling to suggest this customer may churn, hence offer them an incentive to stay.
Increased usage of Real Time data.
End to end Data Lineage automatically captured by the tools. Better metadata management of the systems will mean that users can easily see where the data came from and what transformations it has undergone, improving the trust in the data & reports. Systems will also be self documenting providing users with more help information and simplifying ongoing maintenance.
Integrated, real time Data Quality Management as a means to measure accuracy of operational process performance. This would provide cross system validation, and verify business process performance by monitoring data accuracy, leading to better and more dynamic process modelling, business process re-engineering and hence efficiency gains.
Packaged Analytical Applications like finance systems in the 80's and packaged ERP (Enterprise Requirement Planning) in the 90's. Packaged BI may become the standard for this decade. Why build your own data warehouse and suite of reports and dashboards from scratch when your business is similar to many others? Buy packaged elements and use rapid deployment templates and tools to configure them to meet your precise needs. This rapid deployment capability then supports you as your business evolves.
BI for the masses: As information becomes more critical to manage operational efficiencies, more people need access to that information. Now the BI tools can technically and cost effectively provide more people with access to information, BI for the masses is now reality and can provide significant improvement to a business. The increased presence of Microsoft in the BI space will also increase usage of BI and make it more attractive. BusinessObjects' acquisition of Crystal and recent release of XI will also extend BI to more people, in and outside the organisation - now everyone can be given secure access to information!
Conclusion
The potential benefits from a BI/DWH implementation are huge but far too many companies fail to realise these through: lack of experience, poor design, poor selection and use of tools, poor management of data quality, poor or no project management, limited understanding of the importance of metadata, no realisation that if it is successful it will inevitably evolve and grow, limited awareness of the importance of training..... with all these areas to consider using a specialist consultancy such as IT Performs makes considerable sense.
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