Fundamentals of data engineering

• Verfasst von: Reis, Joe [VerfasserIn]
• Verfasst von: Housley, Matthew L. [VerfasserIn]
• Titel: Fundamentals of data engineering
• Mitwirkende: Verner, Adam [ErzählerIn]
• Verf.angabe: Joe Reis, Matt Housley
• Ausgabe: [First edition].
• Verlagsort: [Place of publication not identified]
• Verlag: Ascent Audio
• Jahr: 2023
• Umfang: 1 online resource (1 sound file (17 hr., 30 min.))
• Fussnoten: Online resource; title from title details screen (O'Reilly, viewed November 15, 2023)
• ISBN: 978-1-6637-3235-4
• ISBN: 1-6637-3235-3
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Audiobooks
• K10plus-PPN: 1871286158
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4418429751
• Lokale URL Inst.: Zum Volltext

Abstract

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; and incorporate data governance and security across the data engineering lifecycle.