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

Data analysis

Closely related to generating insights on data and quality is the ability to quickly analyze the imported data. Data analysis is part of the data profiling phase and lets you get a better understanding of the data before you can move to processing your data for ML. SageMaker Data Wrangler includes built-in analyses that help you generate visualizations and data analyses in a few clicks. In addition, you can also create your own custom analysis using custom code. Using data visualizations, you can get a quick overview of your entire dataset. It provides an accessible way to see and understand trends, outliers, and patterns in data. Data Wrangler provides out-of-the-box analysis tools, including histograms and scatter plots. You can create these visualizations with a few clicks and customize them with your own code. In addition to the visualizations, under analysis, you can also create table summaries. Table summaries enable data practitioners to quickly summarize your...