Data Analytics in the AWS Cloud: Building a Data P Format: Paperback
Language: English
Published by John Wiley and Sons, 2023
- Softcover
- New

Condition: New
US$ 41.69
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Add to basketSeller Inventory # 9781119909248
- Title
- Data Analytics in the AWS Cloud: Building a Data P Format: Paperback
- Author
- Joe Minichino
- Publisher
- John Wiley and Sons
- Publication year
- 2023
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1119909244
- ISBN 13
- 9781119909248
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.
"Synopsis" may belong to another edition of this title.
About the Author
GIONATA “JOE” MINICHINO is Principal Software Engineer and Data Architect on the Data & Analytics Team at Teamwork. He specializes in cloud computing, machine/deep learning, and artificial intelligence and designs end-to-end Amazon Web Services pipelines that move large quantities of diverse data for analysis and visualization.
"About the title" may belong to another edition of this title.
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