The Three-Stage Evolution of an Enterprise Data Warehouse

by Mark Fung-A-Fat

After four decades of failing to manage data assets in an enterprise-wide fashion, organizations are suffering from data chaos. As a result, they are unable to determine the true value of their customers, gauge business unit and enterprise performance, react to market conditions quickly and accurately, and -- in some cases -- even stay in business. So how can IT best support business decision making in the current data morass? Must we commit to the painfully slow and costly process of building and maintaining a data warehouse (DW), or will that leave behind too many business units that need their data "yesterday"? If we attempt BI without a DW, will we simply spawn more BI silo applications, making our present data woes even worse?

In this issue, we'll look at both sides of the BI debate. Hear from one author who claims the "democratization" of BI has made the enterprise-wide DW irrelevant. You'll hear from others who predict "serious negative consequences" if organizations abandon the DW -- and argue that agile data techniques allow you to throw out the "bureaucratic bathwater" while keeping the DW "baby." Whether you consider the DW an unnecessary impediment or BI's best hope, you'll find plenty of thought-provoking discussion in this issue of Cutter IT Journal .

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The Three-Stage Evolution of an Enterprise Data Warehouse1 April 2008

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