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
One Big Table OBT Methodology
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- The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition, Ralph Kimball, Margy Ross, 2013 (John Wiley & Sons) - Describes the principles of dimensional modeling, offering context for the normalization that OBT's denormalization contrasts with.
- Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, Martin Kleppmann, 2017 (O'Reilly Media) - Offers fundamental principles of data storage, processing, and system design, which helps understand the architectural advantages and challenges of various data models, including highly denormalized structures.
- Optimizing schema design for BigQuery, Google Cloud Documentation, 2024 (Google Cloud) - Provides official guidance on leveraging BigQuery's columnar architecture for analytical workloads, including denormalization strategies.
- Designing tables for performance, Snowflake Documentation, 2024 - Offers guidance on optimizing table structures for Snowflake's architecture, including considerations for denormalization to enhance query speed.
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