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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
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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

SageMaker Studio setup prerequisites

SageMaker Data Wrangler is available as a service within Amazon SageMaker Studio. While you can still use some of the SageMaker Data Wrangler features via APIs, for the purposes of this book, we will be using Data Wrangler from within SageMaker Studio. In this section, we will cover a brief overview of SageMaker Studio and how to set up a SageMaker Studio domain and users in your AWS account.

Prerequisites

Before we can start setting up SageMaker Studio, there are a few prerequisites, as follows:

  • An AWS account.
  • An Identity and Access Management (IAM) role with the appropriate policy and permissions attached. There is an AmazonSageMakerFullAccess AWS managed policy that you can use as is or as a starting point to create your custom policy.

Studio domain

You will start by creating and onboarding a SageMaker domain using the AWS console. A SageMaker domain includes an Amazon Elastic File System (Amazon EFS) volume, a list...

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