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

The features of AWS SDK for pandas with different AWS services

We will now explore the integration of the awswrangler package with AWS services. awswrangler works with more AWS services, and we explained its integration with some commonly used services such as Amazon S3, RDS databases, Amazon Redshift, and Amazon Athena.

Amazon S3

Amazon’s Simple Storage Service (S3) is the largest and most performant object storage service for structured, semi-structured, and unstructured data and the storage service of choice to build a data lake. Amazon S3 allows you to migrate, store, manage, and secure all structured and unstructured data at an unlimited scale. With an S3 data lake, you can break down data silos, analyze diverse datasets, manage data access in one centralized place, and accelerate machine learning. Amazon S3 is secure by design, scalable on demand, and durable against the failure of an entire AWS Availability Zone. You can use AWS native services and integrate with...