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Data Engineering With AWS Easy-to-follow, Hands-on Guide To Build Data Engineering Pipelines Using AWS

      Author: Baturi   |   25 June 2022   |   comments: 0

Data Engineering With AWS Easy-to-follow, Hands-on Guide To Build Data Engineering Pipelines Using AWS
Data Engineering With AWS: Easy-to-follow, Hands-on Guide To Build Data Engineering Pipelines Using AWS by Ashwin Shaffer
English | 2022 | ISBN: N/A | ASIN: B0B4GPJ7S6 | 470 pages | EPUB | 44 Mb
Start your AWS information engineering trip with this easy-to-follow, hands-on overview and also reach holds with fundamental principles via to constructing information engineering pipes using AWS


Secret Attributes
Learn more about common data designs and also contemporary methods to producing worth from huge information
Check out AWS tools for consuming, changing, and also consuming information, as well as for coordinating pipelines
Find out exactly how to designer and also carry out information lakes as well as data lakehouses for large information analytics
Book Summary
Knowing how to designer and apply intricate information pipes is a very in-demand ability. Data designers are responsible for constructing these pipes that ingest, change, as well as join raw datasets - developing brand-new worth from the information at the same time.
Amazon.com Web Services (AWS) offers a variety of tools to streamline a data engineer's work, making it the liked system for performing data engineering jobs.
This book will certainly take you via the services and also the skills you need to designer as well as execute data pipelines on AWS. You'll begin by examining vital information engineering ideas and a few of the core AWS services that create a part of the data engineer's toolkit. You'll after that designer an information pipeline, review raw data sources, transform the information, as well as find out how the changed information is used by different information customers. The book additionally instructs you concerning inhabiting data marts and also information stockrooms in addition to how an information lakehouse fits into the picture. Later on, you'll be presented to AWS tools for examining data, consisting of those for ad-hoc SQL questions and developing visualizations. In the final chapters, you'll comprehend how the power of machine learning and expert system can be utilized to draw new understandings from information.
By the end of this AWS publication, you'll have the ability to perform information engineering jobs and apply an information pipeline on AWS individually.



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