Data Analytics in the AWS Cloud
eBook - ePub

Data Analytics in the AWS Cloud

Building a Data Platform for BI and Predictive Analytics on AWS

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Data Analytics in the AWS Cloud

Building a Data Platform for BI and Predictive Analytics on AWS

About this book

A comprehensive and accessible roadmap to performing data analytics in the AWS cloud

In Data Analytics in the AWS Cloud: Building a Data Platform for BI and Predictive Analytics on AWS, accomplished software engineer and data architect Joe Minichino delivers an expert blueprint to storing, processing, analyzing data on the Amazon Web Services cloud platform. In the book, you'll explore every relevant aspect of data analytics—from data engineering to analysis, business intelligence, DevOps, and MLOps—as you discover how to integrate machine learning predictions with analytics engines and visualization tools.

You'll also find:

  • Real-world use cases of AWS architectures that demystify the applications of data analytics
  • Accessible introductions to data acquisition, importation, storage, visualization, and reporting
  • Expert insights into serverless data engineering and how to use it to reduce overhead and costs, improve stability, and simplify maintenance

A can't-miss for data architects, analysts, engineers and technical professionals, Data Analytics in the AWS Cloud will also earn a place on the bookshelves of business leaders seeking a better understanding of data analytics on the AWS cloud platform.

Frequently asked questions

Yes, you can cancel anytime from the Subscription tab in your account settings on the Perlego website. Your subscription will stay active until the end of your current billing period. Learn how to cancel your subscription.
No, books cannot be downloaded as external files, such as PDFs, for use outside of Perlego. However, you can download books within the Perlego app for offline reading on mobile or tablet. Learn more here.
Perlego offers two plans: Essential and Complete
  • Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
  • Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Both plans are available with monthly, semester, or annual billing cycles.
We are an online textbook subscription service, where you can get access to an entire online library for less than the price of a single book per month. With over 1 million books across 1000+ topics, we’ve got you covered! Learn more here.
Look out for the read-aloud symbol on your next book to see if you can listen to it. The read-aloud tool reads text aloud for you, highlighting the text as it is being read. You can pause it, speed it up and slow it down. Learn more here.
Yes! You can use the Perlego app on both iOS or Android devices to read anytime, anywhere — even offline. Perfect for commutes or when you’re on the go.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Data Analytics in the AWS Cloud by Joe Minichino in PDF and/or ePUB format, as well as other popular books in Computer Science & Data Mining. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Sybex
Year
2023
Print ISBN
9781119909248
eBook ISBN
9781119909255

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Introduction
  5. Chapter 1: AWS Data Lakes and Analytics Technology Overview
  6. Chapter 2: The Path to Analytics: Setting Up a Data and Analytics Team
  7. Chapter 3: Working on AWS
  8. Chapter 4: Serverless Computing and Data Engineering
  9. Chapter 5: Data Ingestion
  10. Chapter 6: Processing Data
  11. Chapter 7: Cataloging, Governance, and Search
  12. Chapter 8: Data Consumption: BI, Visualization, and Reporting
  13. Chapter 9: Machine Learning at Scale
  14. Appendix: Example Data Architectures in AWS
  15. Index
  16. Copyright
  17. About the Author
  18. About the Technical Editor
  19. Acknowledgments
  20. End User License Agreement