Data Engineering for AI : Enhance data persistence strategies for optimal AI and analytical workload performance (English Edition)
Description: Data engineering is the critical discipline of building and maintaining the systems that enable organizations to collect, store, process, and analyze vast amounts of data, especially for advanced applications like AI and ML. It is about ensuring that it is reliable, accessible, and high...
Guardat en:
| Autors principals: | , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New Delhi :
BPB Publications
2025.
Paris : Cyberlibris |
| Accés en línia: | Accès Université d'Orléans et IFPM |
| Nota: |
Couverture. https://static2.cyberlibris.com/books_upload/300pix/9789365893403.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Data Engineering for AI, Enhance data persistence strategies for optimal AI and analytical workload performance (English Edition), Sundeep Goud Katta, Lav Kumar, New Delhi, BPB Publications, 2025, 1 vol. (379 p.), 978-93-6589-340-3 |
Taula de continguts:
- 1. Introduction to Data Engineering in AI
- 2. Managing Data Collection
- 3. Data Ingestion in Action
- 4. Data Storage in Real-time
- 5. Data Processing Techniques and Best Practices
- 6. Data Integration and Interoperability
- 7. Ensuring Data Quality
- 8. Understanding Data Analytics
- 9. Data Visualization and Reporting
- 10. Operational Data Security
- 11. Protecting Data Privacy
- 12. Data Engineering Case Studies