Data Lake Architecture: Designing the Data Lake and Avoiding the Garbage Dump - Couverture souple

Inmon, Bill

Couverture souple

ISBN 10 : 1634621174 ISBN 13 : 9781634621175

Editeur : Technics Publications, 2016

Synopsis

Organizations invest incredible amounts of time and money obtaining and then storing big data in data stores called data lakes. But how many of these organizations can actually get the data back out in a useable form? Very few can turn the data lake into an information gold mine. Most wind up with garbage dumps.

Data Lake Architecture will explain how to build a useful data lake, where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess.

Bill Inmon opened our eyes to the architecture and benefits of a data warehouse, and now he takes us to the next level of data lake architecture.

A propos du livre

À propos de l'auteur

Bill Inmon, the "father of the data warehouse," has written 60 books published in nine languages. ComputerWorld named Bill one of the ten most influential people in the history of the computer profession. Bill's latest adventure is the building of technology known as textual disambiguation.

À propos de la deuxième de couverture

Organizations invest incredible amounts of time and money obtaining and then storing big data in data stores called data lakes. But how many of these organizations can actually get the data back out in a useable form? Very few can turn the data lake into an information gold mine. Most wind up with garbage dumps.Data Lake Architecture will explain how to build a useful data lake, where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for date lake success: metadata, integration mapping, context, and metaprocess.Bill Inmon opened our eyes to the architecture and benefits of a data warehouse, and now he takes us to the next level of data lake architecture.

Détails de l'édition

• Éditeur: Technics Publications
• Date d'édition: 2016
• Langue: anglais
• ISBN 10: 1634621174
• ISBN 13: 9781634621175
• Reliure: Broché
• Nombre de pages: 166
• Coordonnées du fabricant: non disponible
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