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Data Wrangling on AWS

You're reading from Data Wrangling on AWS

Product type Book

Published in Jul 2023

Publisher Packt

ISBN-13 9781801810906

Pages 420 pages

Edition 1st Edition

Languages

Concepts

Authors (3):

Navnit Shukla

Sankar M

Sampat Palani

View More author details

Table of Contents (19) Chapters

Preface

Part 1:Unleashing Data Wrangling with AWS

Chapter 1: Getting Started with Data Wrangling

Part 2:Data Wrangling with AWS Tools

Chapter 2: Introduction to AWS Glue DataBrew

Chapter 3: Introducing AWS SDK for pandas

Chapter 4: Introduction to SageMaker Data Wrangler

Part 3:AWS Data Management and Analysis

Chapter 5: Working with Amazon S3

Chapter 6: Working with AWS Glue

Chapter 7: Working with Athena

Chapter 8: Working with QuickSight

Part 4:Advanced Data Manipulation and ML Data Optimization

Chapter 9: Building an End-to-End Data-Wrangling Pipeline with AWS SDK for Pandas

Chapter 10: Data Processing for Machine Learning with SageMaker Data Wrangler

Part 5:Ensuring Data Lake Security and Monitoring

Chapter 11: Data Lake Security and Monitoring

Index

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Data visualization is the phase where you will create visuals and charts to better communicate the findings of your analysis to business users. A picture is worth a thousand words and an idea/message can be better communicated with charts/dashboards than tables/text data.

Visualization with Python libraries

In this section, we will explore creating dashboards using Python libraries such as matplotlib (https://matplotlib.org/) and Seaborn (https://seaborn.pydata.org/index.html). There are more Python libraries that can help in visualizing data, but we will not compare all those libraries here.

We will use the same sports dataset for this section as well. There are other datasets such as NY taxi trips datasets that we can use to cover different visualization aspects, but we will use the sports data for continuity purposes in this chapter. Let us consider a use case, where we want to visualize the following requirements:

The number of tickets sold on...

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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.

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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.

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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.

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