Data Engineering with Generative and Agentic AI on AWS
portes grátis
Data Engineering with Generative and Agentic AI on AWS
Building an AI-Augmented Data Practice for the Enterprise
Leto, Justin J.
APress
04/2026
341
Mole
Inglês
9798868821981
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
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).
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Data Engineering on AWS;Generative AI for Data Engineering;Agentic AI in the Cloud;AI-Augmented Data Platforms;Enterprise Data Strategy;Modern Data Architectures;Data Lakes and Data Mesh;Retrieval-Augmented Generation (RAG);Autonomous Data Agents;Natural Language Data Interfaces;Cloud Data Engineering;AI in Data Analytics;Scalable Data Pipelines AWS;Real-Time Data Analytics AWS;Data Engineering Career Guide;AI for Business Intelligence;AWS Data Services;Apache Iceberg on AWS;Machine Learning for Data Engineers;AI-Powered Data Solutions
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).
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Data Engineering on AWS;Generative AI for Data Engineering;Agentic AI in the Cloud;AI-Augmented Data Platforms;Enterprise Data Strategy;Modern Data Architectures;Data Lakes and Data Mesh;Retrieval-Augmented Generation (RAG);Autonomous Data Agents;Natural Language Data Interfaces;Cloud Data Engineering;AI in Data Analytics;Scalable Data Pipelines AWS;Real-Time Data Analytics AWS;Data Engineering Career Guide;AI for Business Intelligence;AWS Data Services;Apache Iceberg on AWS;Machine Learning for Data Engineers;AI-Powered Data Solutions
