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
Accumulating Snapshot Fact Tables
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- The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, Ralph Kimball, Margy Ross, 2013 (Wiley) - This foundational text for dimensional modeling offers comprehensive guidance on fact table design, including detailed explanations of accumulating snapshot fact tables, their architecture, and analytical uses.
- C-Store: A Column-oriented DBMS, Michael Stonebraker, Daniel J. Abadi, Adam Batkin, Xuedong Chen, Mitch Cherniack, Miguel Ferreira, Edmond Lau, Amerson Lin, Samuel Madden, Elizabeth J. O'Neil, Patrick E. O'Neil, Alexander Rasin, Nga Tran, Stanley B. Zdonik, 2005 Proceedings of the 31st International Conference on Very Large Data Bases, Vol. 2 (ACM) DOI: 10.1109/VLDB.2005.150 - This seminal paper introduces the design and advantages of column-oriented database systems, explaining the architecture that influences performance characteristics for operations like updates in analytical workloads.
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