There is a tendency for data warehouse project teams to jump immediately into implementation tasks as the dimensional data model design is finalized. But we’d like to remind you that you’re not quite done when you think you might be. The last major design activity that needs to be completed is a review and validation of the dimensional […]
Yearly Archives: 2008
What does it take to develop a robust dimensional model? Here’s how to get from requirements-gathering to final approval in a process that will ferret out the good, bad and ugly realities of your source data and help you avoid surprises, delays and cost overruns. Kimball Group has written more than 250 Intelligent Enterprise columns and […]
Students often blur the concepts of snowflakes, outriggers, and bridges. In this Design Tip, I’ll try to reduce the confusion surrounding these embellishments to the standard dimensional model. When a dimension table is snowflaked, the redundant many-to-one attributes are removed into separate dimension tables. For example, instead of collapsing hierarchical rollups such as brand and category into columns […]
It’s surprising the number of DW/BI teams that confine the responsibility for designing dimensional models to a single data modeler or perhaps a small team of dedicated data modelers. This is clearly shortsighted. The best dimensional models result from a collaborative team effort. No single individual is likely to have the detailed knowledge of the business requirements and the […]
Ralph’s first article on data warehousing appeared in 1995. During the subsequent 13 years, we’ve written hundreds of articles and Design Tips, as well as published seven books. Remarkably, the concepts that Ralph introduced in the 1990s have withstood the test of time and remain relevant today. However, some of our vocabulary has evolved slightly over the years. This […]
Delivering consistent data is like reaching the top of Mount Everest for most data warehouse initiatives, and data stewards are the climbers who fearlessly strive toward that goal. Achieving data consistency is a critical objective for most DW/BI programs. Establishing responsibility for data quality and integrity can be extremely difficult in many organizations. Most operational systems effectively capture key […]