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Data Wrangling on AWS
Data Wrangling on AWS

Data Wrangling on AWS: Clean and organize complex data for analysis

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Profile Icon Shukla Profile Icon Sankar M Profile Icon Sam Palani
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₱1468.99 ₱1632.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (8 Ratings)
eBook Jul 2023 420 pages 1st Edition
eBook
₱1468.99 ₱1632.99
Paperback
₱2040.99
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Free Trial
Arrow left icon
Profile Icon Shukla Profile Icon Sankar M Profile Icon Sam Palani
Arrow right icon
₱1468.99 ₱1632.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (8 Ratings)
eBook Jul 2023 420 pages 1st Edition
eBook
₱1468.99 ₱1632.99
Paperback
₱2040.99
Subscription
Free Trial
eBook
₱1468.99 ₱1632.99
Paperback
₱2040.99
Subscription
Free Trial

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Data Wrangling on AWS

Getting Started with Data Wrangling

In the introductory section of this book, we listed use cases regarding how organizations use data to bring value to customers. Apart from that, organizations collect a lot of other data so that they can understand the finances of customers, which helps them share it with stakeholders, including log data for security, system health checks, and customer data, which is required for working on use cases such as Customer 360s.

We talked about all these use cases and how collecting data from different data sources is required to solve them. However, from collecting data to solving these business use cases, one very important step is to clean the data. That is where data wrangling comes into the picture.

In this chapter, we are going to learn the basics of data wrangling and cover the following topics:

  • Introducing data wrangling
  • The steps involved in data wrangling
  • Best practices for data wrangling
  • Options available within Amazon Web Services (AWS) to perform data wrangling
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Key benefits

  • Execute extract, transform, and load (ETL) tasks on data lakes, data warehouses, and databases
  • Implement effective Pandas data operation with data wrangler
  • Integrate pipelines with AWS data services

Description

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.

Who is this book for?

This book is for data engineers, data scientists, and business data analysts looking to explore the capabilities, tools, and services of data wrangling on AWS for their ETL tasks. Basic knowledge of Python, Pandas, and a familiarity with AWS tools such as AWS Glue, Amazon Athena is required to get the most out of this book.

What you will learn

  • Explore how to write simple to complex transformations using AWS data wrangler
  • Use abstracted functions to extract and load data from and into AWS datastores
  • Configure AWS Glue DataBrew for data wrangling
  • Develop data pipelines using AWS data wrangler
  • Integrate AWS security features into Data Wrangler using identity and access management (IAM)
  • Optimize your data with AWS SageMaker

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 31, 2023
Length: 420 pages
Edition : 1st
Language : English
ISBN-13 : 9781801817660
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Product Details

Publication date : Jul 31, 2023
Length: 420 pages
Edition : 1st
Language : English
ISBN-13 : 9781801817660
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Amazon
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Concepts :
Tools :

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Frequently bought together


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Total 7,246.97 Stars icon

Table of Contents

18 Chapters
Part 1:Unleashing Data Wrangling with AWS Chevron down icon Chevron up icon
Chapter 1: Getting Started with Data Wrangling Chevron down icon Chevron up icon
Part 2:Data Wrangling with AWS Tools Chevron down icon Chevron up icon
Chapter 2: Introduction to AWS Glue DataBrew Chevron down icon Chevron up icon
Chapter 3: Introducing AWS SDK for pandas Chevron down icon Chevron up icon
Chapter 4: Introduction to SageMaker Data Wrangler Chevron down icon Chevron up icon
Part 3:AWS Data Management and Analysis Chevron down icon Chevron up icon
Chapter 5: Working with Amazon S3 Chevron down icon Chevron up icon
Chapter 6: Working with AWS Glue Chevron down icon Chevron up icon
Chapter 7: Working with Athena Chevron down icon Chevron up icon
Chapter 8: Working with QuickSight Chevron down icon Chevron up icon
Part 4:Advanced Data Manipulation and ML Data Optimization Chevron down icon Chevron up icon
Chapter 9: Building an End-to-End Data-Wrangling Pipeline with AWS SDK for Pandas Chevron down icon Chevron up icon
Chapter 10: Data Processing for Machine Learning with SageMaker Data Wrangler Chevron down icon Chevron up icon
Part 5:Ensuring Data Lake Security and Monitoring Chevron down icon Chevron up icon
Chapter 11: Data Lake Security and Monitoring Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9
(8 Ratings)
5 star 87.5%
4 star 12.5%
3 star 0%
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Miroslaw Banasiak Feb 15, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Feefo Verified review Feefo
Gagan Brahmi Apr 12, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very impressed with the breadth of topics this book covers. I have been in data space for more than decade and I throughly concur to all the aspects covered by this book when it comes to working with data on AWS. The book is useful for everyone including the beginners or seasoned professionals. I'd highly recommend this book to better understand the data manipulation techniques using AWS platform.
Amazon Verified review Amazon
Pavan Pusuluri Sep 28, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Data Wrangling on AWS" provides a comprehensive and insightful guide to the intricate world of data management within Amazon Web Services (AWS). This book demystifies the complexities of data wrangling, making it accessible to both newcomers and seasoned professionals.One of the standout features of the book is its ability to address a wide spectrum of users. Whether you're a data engineer, data scientist, or business analyst, the book caters to your specific needs by offering relevant insights and real-world scenarios.From extracting data from various sources to performing data cleansing and shaping operations, the book's step-by-step approach ensures that you're equipped to handle diverse data challenges.Whether you're aiming to refine your data management skills or seeking to unlock the power of AWS for your data driven endeavors, this book serves as an invaluable companion on your journey !
Amazon Verified review Amazon
Naresh Aug 22, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is one of the most precise and curated version of a book which deals with complex data sets. If you deal with data this book is the one to read and understand the concepts of data analysis in depth
Amazon Verified review Amazon
Om S Aug 11, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
"Data Wrangling on AWS" offers an insightful journey into the realm of data transformation, redefining raw and unruly data into organized, structured information. This review sheds light on the book's key features and invaluable insights!!Effortless ETL Mastery: The book's focus on extract, transform, and load (ETL) tasks across data lakes, warehouses, and databases unlocks a new level of proficiency in data handling.Pandas-Powered Data Operation: With a spotlight on Pandas data operation using data wrangler, readers are empowered to wield the prowess of Python's renowned data manipulation library for effective data wrangling.Seamless AWS Integration: The integration of AWS data services into pipelines is masterfully explained, enabling readers to harness the full potential of AWS in their data wrangling endeavors.The book dives deep into the art of data wrangling, illuminating the significance of cleaning, transforming, and structuring unstructured data. Guided by the book's comprehensive insights, readers are introduced to AWS Glue DataBrew, AWS data wrangler, AWS Sagemaker, and various other services within the AWS ecosystem.The exploration doesn't stop there; advanced topics, including performing Pandas data operations with AWS data wrangler, optimizing ML data using AWS SageMaker, and building data warehouses with Glue DataBrew, are thoroughly covered. Security and monitoring aspects are also thoughtfully addressed, ensuring a holistic understanding of data wrangling.
Amazon Verified review Amazon
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