Back to School: Data Warehousing 101

  Business Intelligence   Strategy  

Almost gone are the dog days of summer. It's time to pack up those lunchboxes and send the kids back to school. Well, it's time for all of us at the gantthead Institute to go back to school, too, and get back to the basics with Data Warehousing 101. I'm sure that all of us IT project managers have had business partners in the past, and often we have had to articulate the concept of a data warehouse to many groups of less tech-savvy individuals. Inevitably, when we start explaining this concept, we get carried away with our tech-speak. We begin to throw in stars and snowflakes and ETL and data marts and ODS--and we confuse the heck out of most. This article is intended to serve as a primer to the technical nuances of data warehousing. It should help you better communicate with the uninitiated.

First of all, data warehousing is a process, not a product or technology. Data warehousing is the process by which data from many operational data sources are integrated into a single data repository (the eponymous data warehouse) that is optimized for analytical purposes. Examples of operational data sources would include the database of an order entry system, claims entry system or purchasing system. Operational systems are typically transaction-based and not designed with analysis in mind, but rather focus on capturing information.

The data warehouse is the cornerstone …

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