Building Scalable Data Warehouses
Chapter 1: MPP Architecture and Storage Internals
Massively Parallel Processing Fundamentals
Decoupling Compute and Storage
Columnar Storage Formats and Compression
Micro-partitioning and Metadata Management
Hands-on practice: Inspecting Storage Profiles
Chapter 2: Advanced Data Modeling at Scale
Dimensional Modeling Constraints in Big Data
Data Vault 2.0 Implementation Patterns
Handling Semi-Structured Data
Schema Evolution and Versioning
Hands-on practice: Designing a Data Vault
Chapter 3: High-Throughput Ingestion Pipelines
Change Data Capture Architectures
Idempotency in Data Pipelines
Micro-batch vs Streaming Ingestion
Handling Late Arriving Data
Hands-on practice: Building a CDC Pipeline
Chapter 4: Query Optimization and Performance Tuning
Analyzing Query Execution Plans
Partition Pruning and Clustering Keys
Join Strategies: Broadcast vs Shuffle
Materialized Views and Caching Layers
Hands-on practice: Tuning High-Latency Queries
Chapter 5: Governance, Security, and Observability
Role-Based Access Control Hierarchies
Dynamic Data Masking and Tokenization
Row-Level Security Implementation
Resource Monitoring and Cost Control
Hands-on practice: Configuring Security Policies
Dynamic Data Masking and Tokenization
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- Dynamic Data Masking, Snowflake Documentation, 2024 (Snowflake) - Offers official guidelines and practical implementation examples for DDM in an MPP data warehouse.
- NIST Special Publication 800-38G: Recommendation for Block Cipher Modes of Operation: Methods for Format-Preserving Encryption, Morris Dworkin and Melvin Young, 2016 NIST Special Publication (National Institute of Standards and Technology (NIST)) DOI: 10.6028/NIST.SP.800-38G - Defines the cryptographic methods for Format-Preserving Encryption (FPE), a key reversible tokenization technique discussed in the section.
- Dynamic data masking for privacy-preserving data processing, Bin Li, Mengyu Zhang, Jiying Wang, and Peng Liu, 2021 Journal of Parallel and Distributed Computing, Vol. 149 (Elsevier) DOI: 10.1016/j.jpdc.2020.12.001 - Discusses the principles, architectures, and challenges of dynamic data masking for privacy in data processing, covering aspects relevant to the section content.
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