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


Welcome to the world of Data Wrangling on AWS! In this comprehensive book, we will explore the exciting field of data wrangling and uncover the immense potential of leveraging Amazon Web Services (AWS) for efficient and effective data manipulation and preparation. Whether you are a data professional, a data scientist, or someone interested in harnessing the power of data, this book will provide you with the knowledge and tools to excel in the realm of data wrangling on the AWS platform.

Data wrangling, also known as data preparation or data munging, is a critical step in the data analysis process. It involves transforming raw data into a clean, structured format that is ready for analysis. With the exponential growth of data and the increasing need for data-driven decision-making, mastering the art of data wrangling has become essential for extracting valuable insights from vast and complex datasets.

In this book, we will guide you through a series of chapters, each focusing on a specific aspect of data wrangling on AWS. We will explore various AWS services and tools that empower you to efficiently manipulate, transform, and prepare your data for analysis. From AWS Glue and Athena to SageMaker Data Wrangler and QuickSight, we will delve into the powerful capabilities of these services and uncover their potential for unlocking valuable insights from your data.

Throughout the chapters, you will learn how to leverage AWS’s cloud infrastructure and robust data processing capabilities to streamline your data-wrangling workflows. You will discover practical techniques, best practices, and hands-on examples that will equip you with the skills to tackle real-world data challenges and extract meaningful information from your datasets.

So, whether you are just starting your journey in data wrangling or looking to expand your knowledge in the AWS ecosystem, this book is your comprehensive guide to mastering data wrangling on AWS. Get ready to unlock the power of data and unleash its full potential with the help of AWS’s cutting-edge technologies and tools.

Let’s dive in and embark on an exciting journey into the world of data wrangling on AWS!