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Pragmatic Business Intelligence and Scorecarding (Part 1)
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There are many other aspects of reporting and information delivery that could be considered in a comprehensive analysis of the topic, but this article will focus on this particular problem and various approaches to addressing it.
The Bottom Up “Enterprise Data Warehouse” Approach
A “bottom up” effort based on the ideal theoretical approach might attempt to create a robust enterprise data warehouse that integrated these many data sources into a unified information foundation. This process would include a staging area and a top-tier ETL tool (for Extracting, Transforming, and Loading data). This ambitious effort would include large amounts of time spent in defining data integration rules, gaining consensus on how do deal with inconsistencies, and addressing a whole host of other challenging issues. Few people would deny that as IT projects grow larger, the time and effort required to get to success seems to grow exponentially. Many enterprise data warehouse projects have ultimately been deemed failures because the scope of the effort resulted in time-frames that were unacceptable (and many IT professionals could attest to the frustration of almost reaching a target, only to find that the target had moved and new data sources had emerged.) The effort to create a comprehensive integrated information foundation also creates a common situation where much of the data that ultimately ends up in the data warehouse rarely gets used to add significant value to the business. Even if, after many months (or years) of effort, the enterprise data warehouse is a technical masterpiece, there still may a big gap between the data warehouse and the end users. Many companies have spent many millions in building a solid data warehouse foundation only to have the business users fail to embrace it. Part of the gap was filled, but a bridge half-way across a wide river is of very limited value. (See Figure 2)
Figure 2
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