David Haertzen, First Place Learning.

Getting the right people involved in your data warehousing and business intelligence project is critical to the success of the effort.  Categories of people that are needed include: executive supporters, business users and technical team members.  When you have read this article you will have greater insight into finding and recruiting the kinds of people needed to make your data warehousing project a success.

First, you need executive supporters and in particular an executive sponsor.  The right executive supporters will ensure that funding is provided and that the organization follows through with the actions and “political will” to succeed.  The ideal data warehousing executive sponsor will have a stake in the success or failure of the effort while having sufficient authority to obtain resources and to enlist the support of the rest of the organization.  Enterprise level BI typically requires a more highly place executive sponsor that a departmental data mart. In order to find the sponsor you may need to enlist the help of key business users who can sell the idea of data warehouse upward through their part of the organization.

Second, you need to have key business users, sometimes known as BI champions, in your corner.  These important business people believe that BI can help the organization and have good ideas about how those benefits can be realized.  Often the BI champions are “power users” who understand the organization’s data as well uses of that data.  For example, the BI champion may be a marketing manager or analyst who needs data to improve marketing campaigns.  This marketing BI champion can help to sell the approach to the marketing management who can in turn educate executive management.

Finally, you need technical team members to create a working solution.  A number of skill sets are needed.  First, enterprise architects are needed to layout the infrastructure for the data warehouse – recommending hardware and software platforms.  Second, business analysts are needed to translate business requirements into a form that the technical team can understand.  Third, data architects are needed to design databases and the data flow required to populate the data warehouse.  Fourth, Extract Transform Load (ETL) developers are needed to build processes that populate the data warehouse.  Fifth, Quality Assurance (QA) specialists test the system.  Sixth, BI developers create queries, reports and other analytics to directly support the business.

In conclusion, the successful project needs the right executive backers, key business users and technical team members to succeed.  Now you have a better understanding of what kind of team must be assembled to produce the desired results for your data warehousing and business intelligence project.

David Haertzen, First Place Learning.

You can improve your odds of bringing in a successful data warehousing project by avoiding critical mistakes that others have made.  In this article, you will learn what these six critical mistakes are and how to avoid them. 

First, create a data warehouse without business input and expect that business users will embrace and use that system.  This “build it and they will come” approach is usually doomed to failure.  There are two reasons why this is a problem.  For one thing, a system developed without business input is unlikely to meet business requirements.  For another thing, business people who are left out will be unlikely to support a system that is pushed at them without their involvement. 

Second, save the most difficult part of the project until the end.  Obtaining the right data is often the most difficult part of the data warehousing and business intelligence project.  If you wait until the end to see what the outputs look like, you may get the nasty surprise that data is not what the business is seeking.  Instead, work to explore data and show parts of the data to business people as early in the project as possible.  Then any problems that are discovered can be more readily corrected.

Third, start without basic pieces in place.  If you start without being ready you run the risk of failure and loss of credibility.  Basic pieces that should be in place include: business sponsor, analytics champions, a specific business goals, and basic technical architecture.

Fourth, wait until conditions are perfect.  It is difficult to find perfect conditions.  It is OK to start in a focused area with basic technology.  Success in one area can be a stepping stone to further success.  If you wait for all conditions to be perfect, you run the risk that your project may never start.

Fifth, set unrealistic expectations with executives.  If you tell executives that the new system will solve all problems you are running the risk that executives will be disappointed when they learn otherwise. 

Sixth and finally, antagonize executives by implying that they are making poor decisions.  If you sell the project by saying that “executives will now be able to make informed decisions”, the executive supporters that you need may think that you are saying that they are uniformed decision makers and then feel antagonistic toward your project.

In conclusion, we have reviewed some basic mistakes that can harm your data warehousing project.  Armed with this information, you can improve your odds of a successful project.

 William (Bill) H. Inmon has provided an alternate and useful definition, “A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision-making process.”