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

Training a machine learning model

We have now used Data Wrangler to do data analysis and processing, which involved several steps, such as data cleaning, preprocessing, feature engineering, and exploratory data analysis. These steps are crucial before doing machine learning, as they ensure that data is in the correct format, we selected the relevant features, and we dealt with outliers and missing values using data transformation. Data Wrangler provides a unified experience, enabling you to prepare data and seamlessly train a machine learning model, all from within the tool.

SageMaker Autopilot is a tool that automates the key tasks of an automatic machine learning (AutoML) process. This includes exploring your data, selecting algorithms relevant to your problem type, and preparing the data to facilitate model training and tuning. With just a few clicks, you can automatically build, train, and tune ML models using Autopilot, XGBoost, or your own algorithm, directly from the Data...