MikeDavisSQL | The Business Intelligence Guy. BI Developer Network Community. Kimball University: The 10 Essential Rules of Dimensional Modeling - Software - Business Intelligence. Follow the rules to ensure granular data, flexibility and a future-proofed information resource. Break the rules and you'll confuse users and run into data warehousing brick walls.A student attending one of Kimball Group's recent onsite dimensional modeling classes asked me for a list of "Kimball's Commandments" for dimensional modeling.
We'll refrain from using religious terminology, but let's just say the following are not-to-be-broken rules together with less stringent rule-of-thumb recommendations. Rule #1: Load detailed atomic data into dimensional structures. Dimensional models should be populated with bedrock atomic details to support the unpredictable filtering and grouping required by business user queries. Users typically don't need to see a single record at a time, but you can't predict the somewhat arbitrary ways they'll want to screen and roll up the details. Rule #2: Structure dimensional models around business processes. 1 of 3 More Insights. Bill Inmon vs. Ralph Kimball. Data Warehousing > Concepts > Bill Inmon vs. Ralph Kimball In the data warehousing field, we often hear about discussions on where a person / organization's philosophy falls into Bill Inmon's camp or into Ralph Kimball's camp.
We describe below the difference between the two. Bill Inmon's paradigm: Data warehouse is one part of the overall business intelligence system. An enterprise has one data warehouse, and data marts source their information from the data warehouse. In the data warehouse, information is stored in 3rd normal form.
Ralph Kimball's paradigm: Data warehouse is the conglomerate of all data marts within the enterprise. There is no right or wrong between these two ideas, as they represent different data warehousing philosophies. Copyright © 2016 1keydata.com All Rights Reserved Privacy Policy About Contact.