Modern Data Architecture in AI : Optimize AI data storage, versioning, and partitioning with lakehouse
Description: Building effective AI solutions demands a robust data architecture capable of handling vast, diverse, and real-time data. This book aims to provide a deep exploration of the tools, technologies, strategies, and best practices that necessitate the design, implementation, and management o...
Uloženo v:
| Hlavní autoři: | , , |
|---|---|
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
New Delhi :
BPB Publications
2025.
Paris : Cyberlibris |
| On-line přístup: | Accès Université d'Orléans et IFPM |
| Poznámka: |
Couverture. https://static2.cyberlibris.com/books_upload/300pix/9789365899771.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Modern Data Architecture in AI, Optimize AI data storage, versioning, and partitioning with lakehouse, Abhik Choudhury, Praneeth Puchakayala, Aishwarya Badlani, New Delhi, BPB Publications, 2025, 1 vol. (403 p.), 978-93-6589-977-1 |
Obsah:
- 1. Introduction to Modern Data Architecture for AI
- 2. Data Collection and Ingestion Strategies
- 3. Data Storage and Management for AI Workloads
- 4. Data Processing and Transformation for AI
- 5. Modern Data Pipeline Management
- 6. Data Governance, Security, and Compliance in AI
- 7. AI Algorithms and Their Impact on Data Architecture
- 8. Scalable Machine Learning Infrastructure
- 9. Real-time AI Systems and Stream Processing
- 10. Data Visualization and Explainable AI
- 11. Emerging Trends in AI Data Architecture