You're reading from Data Wrangling on AWS

Product typeBook

Published inJul 2023

PublisherPackt

ISBN-139781801810906

Edition1st Edition

Tools

AWS

Concepts

Data Analysis

Authors (3):

Navnit Shukla

Sankar M

Sampat Palani

View More author details

Options available for data wrangling on AWS

Depending on customer needs, data sources, and team expertise, AWS provides multiple options for data wrangling. In this section, we will cover the most common options that are available with AWS.

AWS Glue DataBrew

Released in 2020, AWS Glue DataBrew is a visual data preparation tool that makes it easy for you to clean and normalize data so that you can prepare it for analytics and machine learning. The visual UI provided by this service allows data analysts with no coding or scripting experience to accomplish all aspects of data wrangling. It comes with a rich set of common pre-built data transformation actions that can simplify these data wrangling activities. Similar to any Software as a service (SaaS) (https://en.wikipedia.org/wiki/Software_as_a_service), customers can start using the web UI without the need to provision any servers and only need to pay for the resources they use.

SageMaker Data Wrangler

Similar to AWS Glue DataBrew, AWS also provides SageMaker Data Wrangler, a web UI-based data wrangling service catered more toward data scientists. If the primary use case is around building a machine learning pipeline, SageMaker Data Wrangler should be the preference. It integrates directly with SageMaker Studio, where data that’s been prepared using SageMaker Data Wrangler can be fed into a data pipeline to build, train, and deploy machine learning models. It comes with pre-configured data transformations to impute missing data with means or medians, one-hot encoding, and time series-specific transformers that are required for preparing data for machine learning.

AWS SDK for pandas

For customers with a strong data integration team with coding and scripting experience, AWS SDK for pandas (https://github.com/aws/aws-sdk-pandas) is a great option. Built on top of other open source projects, it offers abstracted functions for executing typical data wrangling tasks such as loading/unloading data from various databases, data warehouses, and object data stores such as Amazon S3. AWS SDK for pandas simplifies integration with common AWS services such as Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, DynamoDB, and S3. It also supports common databases such as MySQL and SQL Server.

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Authors (3)

Navnit Shukla

Navnit Shukla is an accomplished Senior Solution Architect with a specialization in AWS analytics. With an impressive career spanning 12 years, he has honed his expertise in databases and analytics, establishing himself as a trusted professional in the field. Currently based in Orange County, CA, Navnit's primary responsibility lies in assisting customers in building scalable, cost-effective, and secure data platforms on the AWS cloud.
Read more about Navnit Shukla

Sankar M

Sankar Sundaram has been working in IT Industry since 2007, specializing in databases, data warehouses, analytics space for many years. As a specialized Data Architect, he helps customers build and modernize data architectures and help them build secure, scalable, and performant data lake, database, and data warehouse solutions. Prior to joining AWS, he has worked with multiple customers in implementing complex data architectures.
Read more about Sankar M

Sampat Palani

Sam Palani has over 18+ years as developer, data engineer, data scientist, a startup cofounder and IT leader. He holds a master's in Business Administration with a dual specialization in Information Technology. His professional career spans across 5 countries across financial services, management consulting and the technology industries. He is currently Sr Leader for Machine Learning and AI at Amazon Web Services, where he is responsible for multiple lines of the business, product strategy and thought leadership. Sam is also a practicing data scientist, a writer with multiple publications, speaker at key industry conferences and an active open source contributor. Outside work, he loves hiking, photography, experimenting with food and reading.
Read more about Sampat Palani

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