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It is a cliché that software developers who become managers never fully let go of their need to program. Like a cough in a concert hall, there is no way to suppress the tickle that says it's time to design something, code it, test it, demo it, tinker and re-design.

This is why I appreciate my current opportunity to delve into the design and development of ACS's nascent Business Intelligence module. At the recent AUG meeting, we discussed the current status. The project holds enough technical challenges to keep me occupied for many months.

The literature on data warehousing and business intelligence is extensive, reflecting the software industry's decades long struggle to coax 'actionable intelligence' from databases that stubbornly conceal what they know behind a façade of obscure names and complex structures. My bookshelf is groaning under a stack of thousand page books explaining Key Performance Indicators, Slowly Changing Dimensions and debating the pros and cons of star schemas vs. snowflake schemas. Historically, many projects have failed.

The good news is that tremendous progress has been made recently. There is a growing consensus on the best methodologies to use to build a robust, scalable data warehouse that can deliver answers to a wide range of marketing and management questions ? including the questions you have yet to formulate. Better still, the software tools are keeping pace with methodological advances. I've been pleased by the solid foundation Microsoft has built into their SqlServer 2008 suite of business intelligence tools.

 

The lurking suspicion that something could be simplified is the world's richest source of rewarding challenges.
-
Edsger Dijkstra
But a sturdy technical infrastructure is not enough. To succeed, a data warehouse must present just the right mix of data elements. Too few, and users cannot find the answers they seek. Too many, and users get lost trying to sift the relevant from the irrelevant.

This is where you come in. Help us define exactly which reports and pivot tables your decision-makers need in order to make your business hum. What data elements are critical for analyzing promotions and products? If you have built your own reporting site, we would appreciate learning from your experience. If you are currently wrestling with data accessibility issues, let us know how we can help. We look forward to hearing from you!



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