Episode 8 — 1.1 Understand Tables and Schemas: Facts, Dimensions, Slowly Changing Dimensions
This episode explains how schemas organize data so reporting and analysis stay consistent, a core theme that appears whenever Data+ DA0-002 asks you to reason about tables, keys, and modeling choices. You will define a schema as the set of rules and structures that describe how data is stored and related, then connect that to fact tables and dimension tables. Facts represent measurable events at a defined grain, while dimensions provide descriptive context such as time, location, customer, or product. You will also introduce slowly changing dimensions as the mechanism for handling attributes that evolve, like a customer address or a product category, without breaking historical reporting. The key outcome is being able to recognize which table type a prompt describes and what risks arise when the grain or keys are misunderstood.
You will apply the concepts through a realistic reporting scenario where totals must reconcile over time. You will practice identifying grain, choosing keys that prevent duplication, and spotting the common failure mode where a join multiplies rows and inflates metrics. You will also compare approaches for tracking dimension changes, focusing on what happens to historical results when attributes overwrite versus when history is preserved. Troubleshooting guidance includes sanity checks using counts and totals before and after joins, and simple documentation practices that keep assumptions visible when teams reuse datasets. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
