Data Modeling & Warehousing
Well-designed dimensional models make a warehouse fast, intuitive, and cheap to query.
Learn it
Study Kimball dimensional modeling: identify a business process, its grain, dimensions, and facts, then assemble a star schema. Contrast this with normalized OLTP design and understand why analytics favors denormalized stars. See how the same model is implemented with a modern tool like dbt.
By the end you’ll be able to
- Distinguish fact and dimension tables in a star schema
- Design a dimensional model for a business process
Free resources
- Holistics — Kimball's Dimensional Data Modeling(opens in a new tab)Start here
Best free conceptual overview of facts, dimensions, star schemas.
Free~30 min - dbt — Building a Kimball Dimensional Model with dbt(opens in a new tab)
Connects the theory to a real modern implementation.
Free~25 min - Data Engineer Camp — dbt Dimensional Modelling(opens in a new tab)
Hands-on repo to build a star schema yourself.
Free~2 hours
Practice
Design a star schema (1 fact + 3-4 dimension tables) in SQL DDL for a retail orders dataset, defining the grain explicitly.
Build it — your output
A star-schema diagram plus CREATE TABLE statements for one fact and its dimensions.
Prove it — check yourself
You’re ready to move on when you can honestly say yes to each:
- Can you define the 'grain' of a fact table and why it matters?
- Can you classify a column as a fact measure or a dimension attribute?
- Can you explain why analytics warehouses denormalize?
Do it with AI
Use a free AI tool as your tutor and pair-programmer. Copy a prompt below into Claude, ChatGPT, or Gemini (for building, try Cursor or Copilot).
The habit: Try it yourself first — a little struggle is where the learning actually happens. Then ask for a hint before the answer — never copy blindly.
- Understand itClaude / ChatGPT / Gemini
I'm a beginner learning "Data Modeling & Warehousing". Explain it in simple terms with a real-world analogy, then ask me ONE question to check my understanding — don't reveal the answer.
- PracticeClaude / ChatGPT / Gemini
Give me 3 short practice problems on "Data Modeling & Warehousing" (my goal: distinguish fact and dimension tables in a star schema), from easy to hard. Don't include the solutions yet — I'll try them first, then ask you to check.
- Get unstuckClaude / ChatGPT / Gemini
I'm stuck on this exercise about "Data Modeling & Warehousing": [paste your attempt here]. Give me ONE small hint to move forward — do NOT give me the full solution.
- Build & reviewCursor / Copilot
Here is my work for a "Data Modeling & Warehousing" task: [paste your code or answer]. Review it: point out what's wrong and WHY, and suggest improvements — but let me make the fixes myself.
- Prove itClaude / ChatGPT / Gemini
Quiz me on "Data Modeling & Warehousing". Ask me 5 questions one at a time, wait for my answer each time, then tell me if I'm right and briefly why.