Serverless ETL and Analytics with AWS Glue: Your comprehensive reference guide to learning about AWS Glue and its features - Softcover

Pathak, Vishal; Vajiraya, Subramanya; Sekiyama, Noritaka; Tanaka, Tomohiro; Quiroga, Albert; Gaur, Ishan

Softcover

ISBN 10: 1800564988 ISBN 13: 9781800564985

Verlag: Packt Publishing, 2022

Inhaltsangabe

Build efficient data lakes that can scale to virtually unlimited size using AWS Glue

Key Features

• Learn to work with AWS Glue to overcome typical implementation challenges in data lakes
• Create and manage serverless ETL pipelines that can scale to manage big data
• Written by AWS Glue community members, this practical guide shows you how to implement AWS Glue in no time

Book Description

Organizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark, enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing, data integration, and building data lakes.

Beginning with AWS Glue basics, this book teaches you how to perform various aspects of data analysis such as ad hoc queries, data visualization, and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You'll find out how data security aspects such as access control, encryption, auditing, and networking are implemented, as well as getting to grips with useful techniques such as picking the right file format, compression, partitioning, and bucketing. As you advance, you'll discover AWS Glue features such as crawlers, Lake Formation, governed tables, lineage, DataBrew, Glue Studio, and custom connectors. The concluding chapters help you to understand various performance tuning, troubleshooting, and monitoring options.

By the end of this AWS book, you'll be able to create, manage, troubleshoot, and deploy ETL pipelines using AWS Glue.

What you will learn

• Apply various AWS Glue features to manage and create data lakes
• Use Glue DataBrew and Glue Studio for data preparation
• Optimize data layout in cloud storage to accelerate analytics workloads
• Manage metadata including database, table, and schema definitions
• Secure your data during access control, encryption, auditing, and networking
• Monitor AWS Glue jobs to detect delays and loss of data
• Integrate Spark ML and SageMaker with AWS Glue to create machine learning models

Who this book is for

This book is for ETL developers, data engineers, and data analysts who want to understand how AWS Glue can help you solve your business problems. Basic knowledge of AWS data services is assumed.

Table of Contents

1. Data Management – Introduction and Concepts
2. Introduction to Important AWS Glue Features
3. Data Ingestion
4. Data Preparation
5. Designing Data Layouts
6. Data Management
7. Metadata Management
8. Data Security
9. Data Sharing
10. Data Pipeline Management
11. Monitoring
12. Tuning, Debugging, and Troubleshooting
13. Data Analysis
14. Machine Learning Integration
15. Architecting Data Lakes for Real-World Scenarios and Edge Cases

Über diesen Titel

Über die Autorinnen und Autoren

Vishal Pathak is a Data Lab Solutions Architect at AWS. Vishal works with customers on their use cases, architects solutions to solve their business problems, and helps them build scalable prototypes. Prior to his journey in AWS, Vishal helped customers implement business intelligence, data warehouse, and data lake projects in the US and Australia.

Subramanya Vajiraya is a Big data Cloud Engineer at AWS Sydney specializing in AWS Glue. He obtained his Bachelor of Engineering degree specializing in Information Science & Engineering from NMAM Institute of Technology, Nitte, KA, India (Visvesvaraya Technological University, Belgaum) in 2015 and obtained his Master of Information Technology degree specialized in Internetworking from the University of New South Wales, Sydney, Australia in 2017. He is passionate about helping customers solve challenging technical issues related to their ETL workload and implementing scalable data integration and analytics pipelines on AWS.

Noritaka Sekiyama is a Senior Big Data Architect on the AWS Glue and AWS Lake Formation team. He has 11 years of experience working in the software industry. Based in Tokyo, Japan, he is responsible for implementing software artifacts, building libraries, troubleshooting complex issues and helping guide customer architectures

Details zur Ausgabe

• Verlag: Packt Publishing
• Erscheinungsdatum: 2022
• Sprache: Englisch
• ISBN 10: 1800564988
• ISBN 13: 9781800564985
• Einband: Tapa blanda
• Anzahl der Seiten: 434
• Kontakt zum Hersteller: Nicht verfügbar