Fundamentals of Data Engineering: Plan and ... by Reis, Joe Paperback / softback

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Características del artículo

Estado
En muy buen estado: Libro que se ha leído y que no tiene un aspecto nuevo, pero que está en un ...
ISBN
1098108302
EAN
9781098108304
Date of Publication
2022-07-05
Release Title
Fundamentals of Data Engineering: Plan and Build Robust Data S...
Artist
Reis, Joe
Brand
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Colour
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Book Title
Fundamentals of Data Engineering: Plan and Build Robust Data S...
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Product Identifiers

Publisher
O'reilly Media, Incorporated
ISBN-10
1098108302
ISBN-13
9781098108304
eBay Product ID (ePID)
17057251431

Product Key Features

Number of Pages
447 Pages
Language
English
Publication Name
Fundamentals of Data Engineering : Plan and Build Robust Data Systems
Subject
Data Modeling & Design, Desktop Applications / Databases, Data Processing, Databases / Data Mining
Publication Year
2022
Type
Textbook
Subject Area
Computers
Author
Joe Reis, Matt Housley
Format
Trade Paperback

Dimensions

Item Height
1.1 in
Item Weight
27 Oz
Item Length
9.2 in
Item Width
7 in

Additional Product Features

LCCN
2023-275148
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
005.743
Synopsis
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology. This book will help you: Get a concise overview of the entire data engineering landscape Assess data engineering problems using an end-to-end framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle
LC Classification Number
QA76.9

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