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Data Wrangling on AWS

You're reading from  Data Wrangling on AWS

Product type Book
Published in Jul 2023
Publisher Packt
ISBN-13 9781801810906
Pages 420 pages
Edition 1st Edition
Languages
Authors (3):
Navnit Shukla Navnit Shukla
Profile icon Navnit Shukla
Sankar M Sankar M
Profile icon Sankar M
Sampat Palani Sampat Palani
Profile icon Sampat Palani
View More author details

Table of Contents (19) Chapters

Preface 1. Part 1:Unleashing Data Wrangling with AWS
2. Chapter 1: Getting Started with Data Wrangling 3. Part 2:Data Wrangling with AWS Tools
4. Chapter 2: Introduction to AWS Glue DataBrew 5. Chapter 3: Introducing AWS SDK for pandas 6. Chapter 4: Introduction to SageMaker Data Wrangler 7. Part 3:AWS Data Management and Analysis
8. Chapter 5: Working with Amazon S3 9. Chapter 6: Working with AWS Glue 10. Chapter 7: Working with Athena 11. Chapter 8: Working with QuickSight 12. Part 4:Advanced Data Manipulation and ML Data Optimization
13. Chapter 9: Building an End-to-End Data-Wrangling Pipeline with AWS SDK for Pandas 14. Chapter 10: Data Processing for Machine Learning with SageMaker Data Wrangler 15. Part 5:Ensuring Data Lake Security and Monitoring
16. Chapter 11: Data Lake Security and Monitoring 17. Index 18. Other Books You May Enjoy

Summary

In this chapter, we covered Apache Spark, its connection with AWS Glue, and the various features available in AWS Glue, including AWS Glue Data Catalog for data discovery, AWS Glue Crawler for metadata extraction, and AWS Glue Studio for building UI-based ETL pipelines. We also explored how to use the AWS Glue Marketplace to subscribe to different connectors so that we can extract data from SaaS applications.

In the next chapter, we will discuss another essential service that plays a significant role in the data wrangling and discovery process: Amazon Athena.

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