Book Image

Data Wrangling on AWS

By : Navnit Shukla, Sankar M, Sam Palani
5 (1)
Book Image

Data Wrangling on AWS

5 (1)
By: Navnit Shukla, Sankar M, Sam Palani

Overview of this book

Data wrangling is the process of cleaning, transforming, and organizing raw, messy, or unstructured data into a structured format. It involves processes such as data cleaning, data integration, data transformation, and data enrichment to ensure that the data is accurate, consistent, and suitable for analysis. Data Wrangling on AWS equips you with the knowledge to reap the full potential of AWS data wrangling tools. First, you’ll be introduced to data wrangling on AWS and will be familiarized with data wrangling services available in AWS. You’ll understand how to work with AWS Glue DataBrew, AWS data wrangler, and AWS Sagemaker. Next, you’ll discover other AWS services like Amazon S3, Redshift, Athena, and Quicksight. Additionally, you’ll explore advanced topics such as performing Pandas data operation with AWS data wrangler, optimizing ML data with AWS SageMaker, building the data warehouse with Glue DataBrew, along with security and monitoring aspects. By the end of this book, you’ll be well-equipped to perform data wrangling using AWS services.
Table of Contents (19 chapters)
1
Part 1:Unleashing Data Wrangling with AWS
3
Part 2:Data Wrangling with AWS Tools
7
Part 3:AWS Data Management and Analysis
12
Part 4:Advanced Data Manipulation and ML Data Optimization
15
Part 5:Ensuring Data Lake Security and Monitoring

Part 1:Unleashing Data Wrangling with AWS

This section marks the beginning of an exciting journey, where we explore the realm of data wrangling and unveil the remarkable capabilities of AWS for data manipulation and preparation. This section lays a solid foundation that provides you with insights into key concepts and essential tools that will pave the way for your data-wrangling endeavors throughout the book.

This part has the following chapter:

  • Chapter 1, Getting Started with Data Wrangling