Data Modeling and Schema Design for Analytics
Chapter 1: Foundations of Analytical Architecture
Operational vs Analytical Workloads
Row-Oriented vs Columnar Storage
The Role of Denormalization
Hands-on Practical: Analyzing Query Plans
Chapter 2: Dimensional Modeling Core
The Grain of Data
Fact Tables Fundamentals
Dimension Tables Structure
Star Schema Architecture
Snowflake Schema Variations
Hands-on Practical: Designing a Star Schema
Chapter 3: Advanced Dimension Handling
Surrogate Keys vs Natural Keys
Slowly Changing Dimensions Type 1
Slowly Changing Dimensions Type 2
Date and Time Dimensions
Role-Playing Dimensions
Hands-on Practical: Implementing SCD Type 2
Chapter 4: Complex Fact Table Patterns
Transactional Fact Tables
Periodic Snapshot Fact Tables
Accumulating Snapshot Fact Tables
Factless Fact Tables
Hands-on Practical: Building an Accumulating Snapshot
Chapter 5: Physical Design and Optimization
Partitioning Strategies
Clustering and Sorting Keys
Nested Data Structures
One Big Table OBT Methodology
Hands-on Practical: Optimization Tuning
Transactional Fact Tables
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- Star Schema The Complete Reference, Christopher Adamson, 2010 (McGraw-Hill Education) - Detailed explanation of star schema design, including the structure and relationships of fact and dimension tables.
- Data Warehouse Design: Modern Principles and Best Practices, Stefano Rizzi, Luca Varesio, Matteo Golfarelli, 2018 (McGraw-Hill Education) - Explores contemporary data warehouse design principles, including physical design considerations such as partitioning for large fact tables.
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