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 […]

Dimensional designs often need to accommodate multivalued dimensions. Patients can have multiple diagnoses. Students can have multiple majors. Consumers can have multiple hobbies or interests. Commercial customers can have multiple industry classifications. Employees can have multiple skills or certifications. Products can have multiple optional features. Bank accounts can have multiple customers. The multivalued dimension challenge […]

Countless organizations have created mature dimensional data warehouses that are considered tremendous successes within their organizations. These data warehouse environments support key reporting and analysis requirements for the enterprise. Many are capable of supporting self-serve data access and analysis capabilities for disparate business users. Nonetheless, regardless of the success achieved by these dimensional data warehouses, […]

There are two powerful ideas at the foundation of most successful data warehouses. First, separate your systems. Second, build stars and cubes. In my previous column, I described a complete spectrum of design constraints and unavoidable realities facing the data warehouse designer. This was such a daunting list that I worried that you would head […]

We are firm believers in the principle that business requirements drive the data model. Occasionally, we’ll work with an organization that needs to analyze Type 2 changes in a dimension. They need to answer questions like “How many customers moved last year?”, or “How many new customers did we get by month?” which can be difficult with the […]

Factless fact table are“fact tables that have no facts but captures the many-to-many relationship between dimension keys.” We’ve previously discussed factless fact tables to represent events or coverage information. An event-based factless fact table is student attendance information; the grain of the fact table is one row per student each day. A typical coverage factless fact […]

This article describes six key decisions that must be made while crafting the ETL architecture for a dimensional data warehouse. These decisions have significant impacts on the upfront and ongoing cost and complexity of the ETL solution and, ultimately, on the success of the overall BI/DW solution. Read on for Kimball Group’s advice on making […]

Over the years, we’ve described common dimensional modeling mistakes, such as our October ’03 “Fistful of Flaws” article in Intelligent Enterprise magazine. And we’ve recommended dimensional modeling best practices countless times; our May ’09 “Kimball’s Ten Rules of Dimensional Modeling” article has been widely read. While we’ve identified frequently-observed errors and suggested patterns, we haven’t […]

Wiley, 2006 Tools and Utilities Corrections In spite of our best efforts, there are a few errors in the book. Here are the major ones we’ve spotted so far, along with the corrected text and/or figures. (Many thanks to the folks who have brought some of these to our attention—we appreciate your careful reading!)

One of the most effective tools for managing data quality and data governance, as well as giving business users confidence in the data warehouse results, is the audit dimension. We often attach an audit dimension to every fact table so that business users can choose to illuminate the provenance and confidence in their queries and […]

The increasingly popular data visualization tools deliver an environment that business analysts love. They provide the ability to define calculations, and more importantly, to explore and experiment with the data. The products have finally innovated away from the old standbys of tables, bar charts, and pie charts, making it easier for users to draw visual […]

Wiley, 2011 Tools and Utilities NOTE: You may need to “Save Link As” to download the files.

The Kimball bus architecture and the Corporate Information Factory: What are the fundamental differences? Based on recent inquiries, many of you are in the midst of architecting (or rearchitecting) your data warehouse. There’s no dispute that planning your data warehouse from an enterprise perspective is a good idea, but do you need an enterprise data […]