Data Engineering with AWS : Acquire the skills to design and build AWS-based data transformation pipelines like a pro, 2/e (Paperback)

Eagar, Gareth

  • 出版商: Packt Publishing
  • 出版日期: 2023-10-31
  • 售價: $1,960
  • 貴賓價: 9.5$1,862
  • 語言: 英文
  • 頁數: 636
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1804614424
  • ISBN-13: 9781804614426
  • 相關分類: Amazon Web Services
  • 海外代購書籍(需單獨結帳)



Looking to revolutionize your data transformation game with AWS? Look no further! From strong foundations to hands-on building of data engineering pipelines, our expert-led manual has got you covered.


Key Features:


  • Delve into robust AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines
  • Stay up to date with a comprehensive revised chapter on Data Governance
  • Build modern data platforms with a new section covering transactional data lakes and data mesh


Book Description:


This book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability.


You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and get acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You'll learn how to ensure strong data governance, and 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. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data mesh, and how to build a cutting-edge data platform on AWS.


By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!


What You Will Learn:


  • Seamlessly ingest streaming data with Amazon Kinesis Data Firehose
  • Optimize, denormalize, and join datasets with AWS Glue Studio
  • Use Amazon S3 events to trigger a Lambda process to transform a file
  • Load data into a Redshift data warehouse and run queries with ease
  • Visualize and explore data using Amazon QuickSight
  • Extract sentiment data from a dataset using Amazon Comprehend
  • Build transactional data lakes using Apache Iceberg with Amazon Athena
  • Learn how a data mesh approach can be implemented on AWS


Who this book is for:


This book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts, while gaining practical experience with common data engineering services on AWS, will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book, but it's not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.



- 深入研究AWS強大的工具,用於數據輸入、轉換、消費和管道編排
- 通過全面修訂的數據治理章節保持最新
- 通過新增的部分,構建現代數據平台,包括事務性數據湖和數據網格

本書由一位擁有25年經驗的資深數據架構師撰寫,旨在幫助您熟練使用AWS生態系統進行數據工程。本修訂版在每一章中都提供了最新的AWS服務和功能更新,重新審視了數據治理,並新增了一個關於構建現代數據平台的全新部分,其中包括實施數據網格方法、開放表格格式(如Apache Iceberg)以及使用DataOps進行自動化和可觀察性。



- 使用Amazon Kinesis Data Firehose無縫地輸入流數據
- 使用AWS Glue Studio優化、去正規化和連接數據集
- 使用Amazon S3事件觸發Lambda過程來轉換文件
- 將數據加載到Redshift數據倉庫並輕鬆運行查詢
- 使用Amazon QuickSight可視化和探索數據
- 使用Amazon Comprehend從數據集中提取情感數據
- 使用Apache Iceberg和Amazon Athena構建事務性數據湖
- 學習如何在AWS上實施數據網格方法