Data Engineering Explained
FAQs
Data engineering is the discipline which creates data collection, storage, transformation, and analysis processes for large amounts of raw data, structured data, semi-structured data, and unstructured data (e.g., big data). Data engineering also encompasses data quality and data access assurance.
- Data extraction/collection
- Data ingestion
- Data storage
- Data transformation
- Data modeling, scaling, and performance
- Data quality and governance
- Data security
- Generalist data engineer
- Pipeline-centric data engineer
- Database-centric data engineer
- Collect
- Move/Store
- Explore/Transform
- Aggregate/Label
- Learn/Optimize
- Python
- SQL
- Golang
- Ruby
- NoSQL
- Perl
- Scala
- Java
- R
- C
- C++
- Data warehousing
- Cloud services
- Data modeling
- Artificial intelligence (AI) and machine learning
- Data pipeline orchestration
- Version control
- Automation
- Containerization
- Streaming data
- Monitoring and logging
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