Data warehousing (DW) and business intelligence (BI) have been evolving and getting more sophisticated over the years. As IT folks, consultants and analysts gain more experience, they often share those experiences when they work at other companies, publish articles or conduct training. By sharing their knowledge, they have helped to improve the overall intelligence of our industry. This has led to the creation of conventional wisdom about how to design, build and deploy DW and BI solutions. This wisdom is a great guide, especially for people who are just getting involved in implementations and don’t yet understand what they need to do. But there is a dark side to conventional wisdom when people treat it like gospel. Too often, people blindly follow the usual advice without making sure that it actually applies to their particular situation. Sometimes you should challenge conventional wisdom. Our industry is still in a stage of active and sometimes turbulent evolution. It’s not always wise to put too much faith in conventional wisdom, especially when the industry is evolving and expanding in ways that could help deliver much more robust performance management, BI and DW solutions.

Conventional wisdom says that DW is independent of applications. Wrong! This is most apparent in financial applications, in particular budgeting, forecasting and planning. Business users need the flexibility to perform a number of iterations on a set of numbers before agreeing to a budget, forecast or plan. They also need to be able to examine historical data to make their projections. But enterprise applications don’t have the capability to do this. And data warehouses can’t meet this need because they aren’t supposed to support applications. So, business users resort to using spreadsheets, which waste their time and productivity. The use of spreadsheets has led to errors and made it impossible to document how the numbers were derived. With the current business and regulatory climate, this is not acceptable for most CFOs. A very effective approach has been to build these financial systems with an application closely linked to the DW. The DW becomes both the system of distribution sending the data to whatever business process or user that needs it as well as the system of record where the “official” budget, forecast or plan is stored. Data flows from source systems to data warehouses, then to data marts and cubes and is finally consumed by BI applications. Every architectural diagram shows this one-way flow. The sources for the DW environment have expanded from back-office to include customer-facing applications, external data exchanged from suppliers and partners and many formerly workgroup or desktop applications. The data flow is from across the enterprise and sometimes beyond. The DW environment has now become the information hub that distributes data from and to many applications and data stores. DW is now the system of distribution to any business process, application or person who needs this information.

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