Some clients and students lament that while they want to deliver and share consistently-defined master conformed dimensions in their data warehouse/business intelligence (DW/BI) environments, it’s “just not feasible.” They explain that they would if they could, but with senior management focused on using agile development techniques to deliver DW/BI solutions, it’s “impossible” to take the […]
Accumulating snapshots are one of the three fundamental types of fact tables. We often state that accumulating snapshot fact tables are appropriate for predictable workflows with well-established milestones. They typically have five to ten key milestone dates representing the workflow/pipeline start, completion, and the key event dates in between. Our students and clients sometimes ask […]
Industry-standard data models are an appealing concept at first blush, but they aren’t the time savers they are cracked up to be. What’s more, these prebuilt models may inhibit data warehouse project success. Vendors and proponents argue that standard, prebuilt models allow for more rapid, less risky implementations by reducing the scope of the data […]
If you’re a long time reader of the Kimball articles, Design Tips and books, you know we feel strongly about the importance of understanding the business’s data and analytic requirements. Suffice it to say that we expect more than merely inventorying the existing reports and data files; we encourage you to immerse yourself in the business community […]
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 […]
A student in a recent Data Warehouse Lifecycle in Depth class asked me for an overview of the Kimball Lifecycle approach to share with their manager. Confident that we’d published an executive summary, I was happy to oblige. Much to my surprise, our only published Lifecycle overview was a chapter in a Toolkit book, so this Design Tip […]
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 […]
Successful data warehouse and business intelligence solutions provide value by helping the business identify opportunities or address challenges. Obviously, it’s risky business for the DW/BI team to attempt delivering on this promise without understanding the business and its requirements. This Design Tip covers basic guidelines for effectively determining the business’s wants and needs. First, start by properly preparing […]
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 […]