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Fundamentals of data engineering /
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 will learn how to plan and build systems to serve the needs of your organization and customers by eva...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media, Inc.,
2022.
|
| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Reis, Joe, |e author. | |
| 245 | 1 | 0 | |a Fundamentals of data engineering / |c Joe Reis and Matt Housley. |
| 250 | |a First edition. | ||
| 264 | 1 | |a Sebastopol, CA : |b O'Reilly Media, Inc., |c 2022. | |
| 300 | |a 1 online resource (204 pages) : |b color illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | |a 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 will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in 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 will understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, governance, and deployment that are critical in any data environment regardless of the underlying technology. This book will help you: Assess data engineering problems using an end-to-end data 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. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Database management. | |
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Data mining. | |
| 650 | 2 | |a Data Mining | |
| 650 | 6 | |a Bases de données |x Gestion. | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 7 | |a Big data |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Database management |2 fast | |
| 700 | 1 | |a Housley, Matt, |e author. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781098108298/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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