Data Engineering Foundations
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Module 1: What Data Engineering Is For
The Job of a Data Pipeline
Preview
Batch, Streaming, and Choosing Between Them
Roles, Tools, and the Modern Stack Without the Hype
3 lessons
Module 2: Data Modeling Fundamentals
Tables, Keys, and Grain
Dimensional Modeling: Facts and Dimensions
Handling Change: Slowly Changing Dimensions and History
3 lessons
Module 3: Ingestion and Storage
Extracting Data from Sources Reliably
Storage Layers: Raw, Staging, and Modeled
File Formats, Partitioning, and Cost Awareness
3 lessons
Module 4: Transformation and Orchestration
Writing Transformations as Code
Orchestration: Dependencies, Schedules, and Retries
Idempotency, Backfills, and Reprocessing
3 lessons
Module 5: Data Quality and Reliability
Testing Data: Schema, Uniqueness, and Business Rules
Monitoring Freshness, Volume, and Anomalies
Incident Response and Root Cause Analysis for Data
3 lessons
Module 6: Operating a Data Platform
Access Control, Privacy, and Sensitive Data
Documentation, Lineage, and Working with Stakeholders
Cost, Performance, and Your Learning Path
3 lessons
Module 1: What Data Engineering Is For
Batch, Streaming, and Choosing Between Them
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