Apress | Practical Data Science: A Guide To Building The Technology Stack For Turning Data Lakes Into Business Assets (2018 EN)

Discussion in 'Computing' started by Kanka, Aug 26, 2019.

  1. Kanka

    Kanka Well-Known Member Loyal User

    Messages:
    16,387
    Likes Received:
    485
    Trophy Points:
    83
    [​IMG]

    Author: Andreas François Vermeulen
    Full Title: Practical Data Science: A Guide To Building The Technology Stack For Turning Data Lakes Into Business Assets
    Publisher: Apress; 1st ed. edition (February 22, 2018)
    Year: 2018
    ISBN-13: 9781484230541 (978-1-4842-3054-1), 9781484230534 (978-1-4842-3053-4)
    ISBN-10: 148423054X, 1484230531
    Pages: 805
    Language: English
    Genre: Educational: Data Mining
    File type: EPUB (True), PDF (True), Code Files
    Quality: 10/10
    Price: 37.44 €


    Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.

    The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions.


    Learn:
    ✓ Become fluent in the essential concepts and terminology of data science and data engineering
    ✓ Build and use a technology stack that meets industry criteria
    ✓ Master the methods for retrieving actionable business knowledge
    ✓ Coordinate the handling of polyglot data types in a data lake for repeatable results

    Features:
    ✓ Provides the essential concepts and terminology to gain fluency in data science and data engineering
    ✓ Walks through the steps of building a technology stack on a layered framework to retrieve actionable business knowledge
    ✓ Teaches how to synthesize the polyglot data types in a data lake with repeatable results

    Who This Book Is For:
    Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers.

    -------------
     
    Last edited by a moderator: Oct 18, 2020