Fundamentals of Data Engineering | Plan and Build Robust Data Systems

Joe Reis (u. a.)

ISBN 10: 1098108302 / ISBN 13: 9781098108304

Published by O'Reilly Media, 2022

About this Item

Fundamentals of Data Engineering | Plan and Build Robust Data Systems | Joe Reis (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | O'Reilly Media | EAN 9781098108304 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Seller Inventory # 121341425

Bibliographic Details

• Title: Fundamentals of Data Engineering | Plan and Build Robust Data Systems
• Publisher: O'Reilly Media
• Publication Date: 2022
• Language: English
• ISBN 10: 1098108302
• ISBN 13: 9781098108304
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 230W x 173H x 25D millimeters 230 millimeters width by 173 millimeters height by 25 millimeters depth
• Weight: 776 grams
• Seller catalogs:
  • Bücher

About this title

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

About the Authors

Joe Reis is a business-minded data nerd who's worked in the data industry for 20 years, with responsibilities ranging from statistical modeling, forecasting, machine learning, data engineering, data architecture, and almost everything else in between. Joe is the CEO and cofounder of Ternary Data, a data engineering and architecture consulting firm based in Salt Lake City, Utah. In addition, he volunteers with several technology groups and teaches at the University of Utah. In his spare time, Joe likes to rock climb, produce electronic music, and take his kids on crazy adventures.

Matt Housley is a data engineering consultant and cloud specialist. After some early programming experience with Logo, Basic, and 6502 assembly, he completed a PhD in mathematics at the University of Utah. Matt then began working in data science, eventually specializing in cloud-based data engineering. He cofounded Ternary Data with Joe Reis, where he leverages his teaching experience to train future data engineers and advise teams on robust data architecture. Matt and Joe also pontificate on all things data on The Monday Morning Data Chat.