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
Hands-on Practical: Building an Accumulating Snapshot
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- The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, Ralph Kimball, Margy Ross, 2013 (John Wiley & Sons) - This foundational book in data warehousing and dimensional modeling offers a comprehensive guide to various fact table types, including a detailed explanation of accumulating snapshot fact tables and their analytical applications.
- MERGE, Snowflake Inc., 2024 (Snowflake Inc.) - Official documentation for the SQL MERGE statement, which is crucial for efficiently updating and inserting data into accumulating snapshot fact tables in modern data warehousing environments like Snowflake.
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