Data Engineering Design Patterns : Scalable data engineering for efficient data systems and workflows
Description: Data engineering has gained even more relevance than before, and data engineering patterns are key to the successful implementation of data engineering projects. This book enables a data engineer to not only become familiar with data engineering patterns but also understand their applic...
Tallennettuna:
| Päätekijät: | , |
|---|---|
| Aineistotyyppi: | Livre numérique |
| Kieli: | Anglais |
| Julkaistu: |
New Delhi :
BPB Publications
2025.
Paris : Cyberlibris |
| Linkit: | Accès Université d'Orléans et IFPM |
| Huomautus: |
Couverture. https://static2.cyberlibris.com/books_upload/300pix/9789365891768.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Data Engineering Design Patterns, Scalable data engineering for efficient data systems and workflows, Amit Kulkarni, Santosh Hegde, New Delhi, BPB Publications, 2025, 1 vol. (411 p.), 978-93-6589-176-8 |
Sisällysluettelo:
- 1. Understanding Data Engineering
- 2. Data Engineering Patterns, Terminologies, and Technical Stack
- 3. Batch Ingestion and Processing
- 4. Real-time Ingestion and Processing
- 5. Micro-batching
- 6. Lambda Architecture
- 7. ETL and ELT
- 8. Data Fundamentals
- 9. Databases and Transactional Data
- 10. Data Warehouse and Data Analytics
- 11. Data Lake and Medallion Architecture
- 12. Data Replication and Partitioning
- 13. Hot Versus Cold Data Storage
- 14. Data Caching and Low Latency Serving
- 15. Data Search Patterns
- 16. Domain Specific Patterns
- 17. Data Security Patterns
- 18. Data Observability and Monitoring Patterns
- 19. Idempotency and Deduplication Patterns
- 20. Data Orchestration Patterns
- 21. Common Performance Pitfalls
- 22. Technology and Infrastructure Selection
- 23. Recap and Next Steps