Many companies began building data warehouses 10 or more years ago. Through considerable trial and error, these veteran companies have established best practices for building, deploying, managing and growing data warehouses and business intelligence applications. Most of these organizations with "mature" data warehousing environments have learned the hard way – they've made similar mistakes and rebounded from them. They have much to teach us about the "dos" and "don'ts" of data warehousing. Last month's column shared two of these mistakes, and two more are featured this month.

Mistake: Not Having Encompassing Architecture with a High Degree of Sharing. Placement of the data warehouse and the potential myriad of other databases (staging, data marts, ODS, etc.) in the data warehouse architecture is always a hot issue. Depending on the scalability of the chosen data warehouse technology, it is usually recommended that the various data warehouse databases be physically independent in separate partitions or machines.

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