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Data Engineering with Generative and Agentic AI on AWS : Building an AI-Augmented Data Practice for the Enterprise.
- Format:
- Book
- Author/Creator:
- Leto, Justin J.
- Series:
- Professional and Applied Computing Series
- Language:
- English
- Subjects (All):
- Amazon Web Services (Firm).
- Generative artificial intelligence.
- Big data.
- Database management.
- Physical Description:
- 1 online resource (461 pages)
- Edition:
- 1st ed.
- Place of Publication:
- Berkeley, CA : Apress L. P., 2026.
- Summary:
- Unlock the future of cloud data engineering with generative and agentic AI on AWS.This hands-on guide shows you how to build intelligent, responsive data platforms using cutting-edge AI capabilities and modern AWS services.
- Contents:
- Chapter 1: Introduction to Data Engineering with Generative and Agentic AI on AWS
- Chapter 2: Data Security and Governance
- Chapter 3: Data Lake Design with Apache Iceberg and S3 Tables
- Chapter 4: Data Mesh Design with Amazon DataZone
- Chapter 5: Big Data Processing and Transformation with AWS Glue and AI Agents
- Chapter 6: Data Pipeline Orchestration and Observability
- Chapter 7: Data Extraction and Enrichment with Generative AI and ML Services
- Chapter 8: Retrieval-Augmented Generation (RAG) with S3 Vectors and Vector Databases
- Chapter 9: Streaming and Real-Time Data Processing
- Chapter 10: Data Warehousing and Text-to-SQL Reporting with Amazon Redshift
- Chapter 11: Generative Business Intelligence with Amazon QuickSight Q
- Chapter 12: Building AI Agents with Bedrock AgentCore, Strands Agents, and Model Context Protocol (MCP).
- Notes:
- Includes index.
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 979-88-6882-199-8
- OCLC:
- 1592688692
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