Fundamentals of Data Engineering | Plan and Build Robust Data Systems

Joe Reis (u. a.)

ISBN 10: 1098108302 / ISBN 13: 9781098108304

Editore: O'Reilly Media, 2022

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Fundamentals of Data Engineering | Plan and Build Robust Data Systems | Joe Reis (u. a.) | Taschenbuch | Kartoniert / Broschiert | 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.

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Dati bibliografici

• Titolo: Fundamentals of Data Engineering | Plan and Build Robust Data Systems
• Editore: O'Reilly Media
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 1098108302
• ISBN 13: 9781098108304
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 230 L x 173 A x 25 P (millimetri) 230 millimetri di larghezza per 173 millimetri di altezza per 25 millimetri di profondità
• Peso: 776 grammi
• Cataloghi dei venditori:
  • Bücher

Descrizione articolo

Riassunto

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