Data Modeling for Analytics
Dimensional design, slowly changing dimensions and the one-big-table debate
By Hamza Chataoui
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About this book
What’s inside
Most warehouse pain traces back to the model, not the tooling. This book teaches dimensional modelling as a practical craft for the cloud-warehouse era — facts and dimensions, grain, slowly changing dimensions, and when a wide denormalised table actually wins. You'll learn to design schemas analysts can navigate without a map and that stay correct as the business changes underneath them.
What you’ll learn
Skills you’ll walk away with
- Pick the right grain for a fact table and never break it
- Design conformed dimensions shared across the business
- Implement Type 1, 2 and 3 slowly changing dimensions
- Model many-to-many relationships with bridge tables
- Decide between star schemas and one-big-table designs
- Handle late-arriving dimensions and dimension reloads
- Translate messy source systems into clean analytical models
Table of contents
9 chapters- 01
Why Modelling Still Matters in the Cloud
- ·Cheap compute, expensive confusion
- ·The analyst as your real user
- ·Symptoms of a bad model
- 02
Facts, Dimensions and Grain
- ·Declaring the grain first
- ·Additive, semi-additive and non-additive facts
- ·Degenerate and factless facts
- 03
Designing Dimensions People Can Use
- ·Attributes and hierarchies
- ·Surrogate keys and natural keys
- ·Conformed dimensions across marts
- 04
Slowly Changing Dimensions in Practice
- ·Type 1, 2 and 3 explained
- ·Effective dates and current flags
- ·Auditing history without bloat
- 05
Many-to-Many and Bridge Tables
- ·When a foreign key is not enough
- ·Weighting factors and allocation
- ·Avoiding double counting
- 06
The One-Big-Table Debate
- ·Denormalisation in columnar stores
- ·Trade-offs in cost and clarity
- ·A pragmatic decision framework
- 07
Late-Arriving Data and Reloads
- ·Late-arriving facts
- ·Late-arriving dimensions
- ·Idempotent rebuilds
- 08
Modelling Messy Source Systems
- ·Taming application databases
- ·Event data into dimensional models
- ·Handling deletes and soft deletes
- 09
Metrics, Semantics and the Final Mile
- ·A single definition per metric
- ·The semantic layer
- ·Documenting the model for analysts
This is the full chapter list — exactly what you’ll receive in the PDF.
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