Building the Data Lakehouse (Technics Publications)
Friday, 01 October 2021

This book describes the features and architecture of the data lakehouse, along with its analytical infrastructure; the next generation of the data warehouse and data lake. Bill Inmon, Mary Levins and Ranjeet Srivastava describe how data lakehouses are designed for use with analytics, machine learning, and data science and also discuss how the universal common connector blends structured, textual, analog, and IoT data.

<ASIN:1634629663>

 

Author: Bill Inmon, Mary Levins and Ranjeet Srivastava
Publisher: Technics Publications
Date: October 2021
Pages: 254
ISBN: 978-1634629669
Print: 1634629663
Kindle: ‎ B09GRZ9KP3
Audience: data scientists
Level: Intermediate
Category: Data Science

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

 

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Machine Learning Q and AI (No Starch Press)

Author: Sebastian Raschka
Publisher: No Starch Press
Date: April 2024
Pages: 264
ISBN: 978-1718503762
Print: 1718503768
Kindle: B0CKKXCK3T
Audience: Developers interested in AI
Rating: 4
Reviewer: Mike James
Q and AI, a play on Q&A is a clever title, but is the book equally clever?



Oracle PL/SQL By Example, 6th Ed

Author: Elena Rakhimov
Publisher: Oracle Press
Pages: 480
ISBN: 978-0138062835
Print: 0138062838
Audience: Developers interested in Oracle PL/SQL
Rating: 4
Reviewer: Kay Ewbank

This is the sixth edition of a well established title that has been updated for the latest version of PL/SQL (21c).


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