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Introduction to Data Engineering
Data Engineering is not about dashboards, ML hype, or random Spark jobs. It’s about building reliable systems that move, transform, and serve data at scale. If software engineering builds products, data engineering builds data infrastructure that products, analytics, and ML depend on.
At its core, data engineering answers three hard questions:
- How does data enter the system
- How does it move and change
- How do we trust it when it’s used
Everything else is implementation detail.
Datasources could be API, CSV, Parquet or JSON.
The data is handled in large volume.
Data Engineering is all about learning how to handle
- Millions of records
- Partial failures
- Schema drifts
- Late arrival data
- Handle duplicate data