Book Image

Data Wrangling on AWS

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

Data Wrangling on AWS

5 (1)
By: Navnit Shukla, Sankar M, Sampat 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)
Part 1:Unleashing Data Wrangling with AWS
Part 2:Data Wrangling with AWS Tools
Part 3:AWS Data Management and Analysis
Part 4:Advanced Data Manipulation and ML Data Optimization
Part 5:Ensuring Data Lake Security and Monitoring

Working with Amazon S3

In previous chapters, we repeatedly discussed the concepts of big data and data lakes and how organizations are using them to store and extract valuable insights from their data through various data wrangling processes, as outlined in Chapter 1, using Amazon Web Services (AWS) services such as AWS Glue DataBrew, the AWS SDK for Pandas, and SageMaker Data Wrangler. This chapter will delve deeper into the specifics of big data and data lakes.

Specifically, we will be covering the following topics:

  • The definition and concept of big data
  • The characteristics of big data
  • The concept and definition of a data lake
  • Best practices for building a data lake on Amazon Simple Storage Service (Amazon S3)
  • The layout and organization of data on Amazon S3

We will begin by exploring the definition and characteristics of big data.