Data Wrangling on AWS
Clean and organize complex data for analysis
Created by Navnit Shukla, Sam Palani, Sankar M
Learn how to clean, transform, and organize complex data using AWS tools and services. Gain practical skills to handle messy or unstructured data and prepare it for analysis, even when working with multiple sources. Build confidence in managing data workflows on AWS for analytics and machine learning.
Packt | Jul 2023 | 420 min
What You Will Learn
You will work through hands-on exercises that guide you from connecting to AWS data sources to building and automating data pipelines. Along the way, you will use AWS Glue DataBrew, AWS data wrangler, and SageMaker to tackle real-world data wrangling tasks. Each step builds your confidence with practical, actionable skills.
Key Features
- Clean, transform, and organize raw data using AWS Glue DataBrew and AWS data wrangler
- Build and automate data pipelines for analytics and machine learning on AWS
- Apply security best practices and optimize data workflows with AWS services
Target Audience
Ideal for data engineers, data scientists, and business analysts who already know Python and Pandas and have some experience with AWS tools. If you want to streamline ETL tasks, improve data quality, and leverage AWS for scalable data workflows, you will find this training especially useful.
