Data Warehousing 101: Pitfalls to Avoid

Sometimes technology gets in the way of getting things done, and us tekkies must do what we can to make our data warehouse work for the purpose it is intended. Ralph Kimball makes 10 good points about the common pitfalls to avoid when implementing a data warehouse, as listed in his book "The Data Warehouse Toolkit", published by Wiley.

• Become immersed with technology rather than the requirements and the goals of business;
• Fail to recruit an influential and accessible management visionary to sponsor the data warehouse;
• Turn this into a multi-year project instead of pursuing manageable iterative development;
• Run out of budget while creating a normalized data structure, before building a viable presentation area;
• Pay more attention to back-room ease of development over front-room ease of use and query performance;
• Make queryable data in presentation area too complex, thus causing users to refer to developers;
• Populate dimensional models on a standalone basis without regard to the data architecture that ties them together;
• Load only summarized data into presentation area's dimensional tables;
• Presume that the business, its requirements and analytics and the underlying data and technology are static;
• Neglect to acknowled that data warehouse success is tied directly to user acceptance.

Next: using MySQL and php to extract, transform and load data (ETL) into the warehouse

Until Next Time,
David