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Data Engineering with AWS

Gareth Eagar (Autor)

Packt Publishing (Editora)

R$ 506,55
SKU: 9781800560413

The missing expert-led manual for the AWS ecosystem - go from foundations to building data engineering pipelines effortlessly

Purchase of the print or Kindle book includes a free eBook in the PDF format.


Key Features:

  • Learn about common data architectures and modern approaches to generating value from big data
  • Explore AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines
  • Learn how to architect and implement data lakes and data lakehouses for big data analytics

 

Book Description:

Knowing how to architect and implement complex data pipelines is a highly sought-after skill. Data engineers are responsible for building these pipelines that ingest, transform, and join raw datasets - creating new value from the data in the process.

Amazon Web Services (AWS) offers a range of tools to simplify a data engineer's job, making it the preferred platform for performing data engineering tasks.

This book will take you through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. The book also teaches you about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data.

By the end of thi

Sobre o Livro

Plataformas AWS e serviços como ingestão, transformação e orquestração são apresentados com foco na construção de pipelines de dados escaláveis e confiáveis.

O texto aborda arquiteturas de data lake e data lakehouse, além de técnicas para popular data marts e armazéns de dados; inclui exemplos práticos de uso de ferramentas para consultas SQL e visualização. A análise incorpora também a aplicação de machine learning para extrair insights a partir dos dados transformados.

Leitores encontrarão orientações sobre como conectar fontes de dados brutas, processá-las e disponibilizar conjuntos prontos para consumo por diferentes clientes analíticos, com atenção a operações e governança.

Características

Categoria Computação
Subcategoria Engenharia de Software
Autores Gareth Eagar
Sobre o Autor
Idioma Inglês
Quantidade de Páginas 482
Acabamento Brochura
Editora Packt Publishing
ISBN 9781800560413
Tamanho 19.1x23.5
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