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.
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Customer ReviewsMost Helpful
By Greg on 17-10-16
Not useful in audio format
Decent content but some chapters were mainly reading out tables verbatim, it was not useful
2 of 2 people found this review helpful
By Erick on 23-03-18
A great inspiration and insights to data lake design. a must read for everyone building a data lake