Data Architecture: full course guide
Dimensional modelling, key stability, conformed dimensions and data contracts, with the ingestion, quality, governance and cost decisions that decide whether a warehouse can be trusted.
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What is inside this guide
01The Data Architect's Remit
- What a Data Architect Owns That an Engineer Does Not
- Modelling the Business Before Modelling the Data
- Grain, Cardinality and the Questions a Model Can Answer
- Architecture Styles: Warehouse, Lake, Lakehouse and Mesh
- Choosing Between Normalised and Dimensional Design
02Dimensional Modelling in Practice
- Facts and Dimensions: Declaring the Grain First
- Additive, Semi-Additive and Non-Additive Measures
- Slowly Changing Dimensions: Types 1, 2 and 3
- Bridge Tables, Multi-Valued Dimensions and Allocation Weights
- Degenerate, Junk and Role-Playing Dimensions
03Keys, Identity and Referential Integrity
- Natural Keys, Surrogate Keys and Why Stability Matters
- Key Generation: Sequences, Hashes and Distributed Identity
- Late-Arriving Dimensions and Inferred Members
- Entity Resolution and Master Data Management
- Enforcing Integrity Without Database Constraints
04Conformance and the Shared Vocabulary
- Conformed Dimensions and the Enterprise Bus Matrix
- Metric Definitions and the Semantic Layer
- Data Contracts Between Producers and Consumers
- Schema Evolution and Backward Compatibility
- Cataloguing, Lineage and Discoverability
05Ingestion, Storage and Physical Design
- Batch, Micro-Batch and Streaming Ingestion Trade-Offs
- Change Data Capture and Idempotent Loading
- File Formats, Partitioning and Clustering
- Open Table Formats: Delta, Iceberg and Hudi
- Physical Layout for Query Cost and Performance
06Data Quality, Testing and Observability
- Defining Quality: Completeness, Validity, Timeliness, Uniqueness
- Testing Data Pipelines: Unit, Contract and Reconciliation Tests
- Freshness, Volume and Distribution Monitoring
- Reconciliation Against Source Systems
- Incident Response for Data: Backfills and Restatements
07Governance, Privacy and the Economics of Data
- Classification, Access Control and Least Privilege
- PII, Retention and the Right to Erasure
- Auditability and Regulatory Evidence
- Cost Models: Storage, Compute and Query Attribution
- Decision Records and Governing a Shared Model
08Serving, Consumption and Evolution
- Reverse ETL and Operational Analytics
- Feature Stores and Training/Serving Skew
- Low-Latency Serving: Caches, Key-Value Stores and APIs
- Self-Service Analytics Without Losing the Vocabulary
- Migrating a Warehouse Without Stopping the Business
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