Outrigger and Mini-Dimensions

Concepts covered: dmScdStrategy

The interviewer will push back on your dimension design: 'This dimension has 50 columns and half of them change weekly. How do you handle that?' This tests whether you know the mini-dimension pattern. Candidates who say 'just apply Type 2 to everything' reveal they have never calculated the storage cost of that approach. The Problem the Interviewer Describes State the problem with numbers: 'A dim_customer with 50 columns, 12 of which change weekly. With Type 2 on all 12, that is 10 million customers times 3 weekly changes times 50 weeks: 1.5 billion rows per year. The dimension becomes unjoinable.' The interviewer is checking whether you can calculate the storage cost of a design decision before committing to it. 1.5B Mini-Dimensions: The Answer That Shows You Know Kimball Your mini-dimens

About This Interactive Section

This section is part of the Conformed and Role-Playing Dimensions: Advanced lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

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DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.