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Data Wrangling on AWS

You're reading from   Data Wrangling on AWS Clean and organize complex data for analysis

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Product type Paperback
Published in Jul 2023
Publisher Packt
ISBN-13 9781801810906
Length 420 pages
Edition 1st Edition
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Authors (3):
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Sankar M Sankar M
Author Profile Icon Sankar M
Sankar M
Navnit Shukla Navnit Shukla
Author Profile Icon Navnit Shukla
Navnit Shukla
Sam Palani Sam Palani
Author Profile Icon Sam Palani
Sam Palani
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1:Unleashing Data Wrangling with AWS
2. Chapter 1: Getting Started with Data Wrangling FREE CHAPTER 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

Understanding Amazon Athena

Amazon Athena is an interactive, serverless analytical service that can help to explore data available in Amazon S3 without loading the data. Athena helps to analyze the data through SQL syntax or interactive Spark applications. It can help customers to analyze datasets stored in multiple data formats on Amazon S3 through familiar SQL. Since Athena is a serverless offering, users are charged based on the data scanned by the queries and there is no need to maintain separate servers to enable user queries. This has enabled business and analytics teams to quickly analyze, transform, and visualize data in the data lake for specific use cases without relying on the data engineering team to come up with complex ETL pipelines.

Amazon Athena was launched on re:Invent 2016 and has gone through significant improvements over the course of time. It was launched as a serverless mechanism to query Amazon S3 data using managed Presto servers from the Athena catalog...

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