Data Governance, Quality, and Observability in Production
Chapter 1: Foundations of Data Governance Code
Defining Governance in Engineering Terms
Data Classification and Tagging Strategies
Role-Based Access Control Models
Policy-as-Code Architectures
Practice: Implementing Access Policies
Chapter 2: Data Quality Dimensions and Testing
Core Dimensions of Data Quality
Anatomy of a Data Assertion
Validating Schemas and Types
Statistical Profiling and Distribution Checks
Practice: Writing Data Validation Suites
Chapter 3: Data Observability Systems
The Pillars of Data Observability
Monitoring Freshness and Latency
Volume and Row Count Anomalies
Schema Drift Detection
Practice: Building a Freshness Monitor
Chapter 4: Data Lineage and Metadata Management
Static vs Dynamic Lineage
The OpenLineage Standard
Dependency Graph Construction
Impact Analysis Techniques
Practice: Extracting Lineage from Logs
Chapter 5: Automated Reliability in CI Pipelines
Pre-commit Hooks for Data Code
Implementing Quality Gates
Circuit Breakers in Pipelines
Alerting and Incident Management
Practice: Configuring a CI Data Test
Role-Based Access Control Models
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- Role-Based Access Control Models, Ravi S. Sandhu, Edward J. Coyne, Hal L. Feinstein, Charles E. Youman, 1996 Computer, Vol. 29 (IEEE) DOI: 10.1109/2.47955 - Classic paper introducing fundamental concepts and architectures of Role-Based Access Control, including role hierarchies, which formed the basis for many subsequent standards and implementations.
- Access Control in Snowflake, Snowflake Inc., 2024 - Official documentation providing practical guidance on implementing Role-Based Access Control, hierarchical roles, and the distinction between functional and access roles within a leading cloud data warehouse.
- Data Mesh: Delivering Data-Driven Value at Scale, Zhamak Dehghani, 2022 (O'Reilly Media) - This book introduces the data mesh paradigm, advocating for decentralized data governance and the use of policy-as-code to manage access control for data products, which aligns with scalable, production-grade data platforms.
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