Practical data science : a guide to building the technology stack for turning data lakes into business assets

Book Cover
Average Rating
Author
Vermeulen, Andreas François,
Published
[New York, New York] : Apress, [2018].
Status
Available Online

Description

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.What You'll 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 ofpolyglot data types in a data lake for repeatable results
Who This Book Is ForData 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

More Details

Format
Language
English
ISBN
9781484230541, 148423054X, 1484230531, 9781484230534

Notes

General Note
Includes index.
Description
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. What You'll 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.
Local note
O'Reilly O'Reilly Online Learning: Academic/Public Library Edition

Discover More

Also in this Series

Checking series information...

More Like This

  • Salesforce DevOps for architects: discover tools and techniques to optimize the delivery of your Salesforce projects Cover
  • Make your data speak: creating actionable data through Excel for non-technical professionals Cover
  • Principles of data science: a beginner's guide to statistical techniques and theory to build effective data-driven applications Cover
  • Data science from scratch: first principles with Python Cover
  • Learn blockchain by building one: a concise path to understanding cryptocurrencies Cover
  • SALESFORCE DATA ARCHITECTURE AND MANAGEMENT: a pragmatic guide for aspiring salesforce... architects and developers to manage, govern, and s Cover
  • Data Science Programming All-In-One for Dummies Cover
  • Data Modeling with Microsoft Power BI: self-service and enterprise data warehouse with power BI Cover
  • A textbook of data structures and algorithms: 3 :mastering advanced data structures and algorithm design strategies Cover
  • Think Julia: how to think like a computer scientist Cover
  • Functional data structures in R: advanced statistical programming in R Cover
  • The Packer Book Cover
  • Hands-on data structures and algorithms with Python: write complex and powerful using the latest features of Python 3.7 Cover
  • Predicting the unknown: the history and future of data science and artificial intelligence Cover
  • Data-oriented programming: reduce software complexity Cover
  • Hands-on dependency injection in Go: develop clean Go code that is easier to read, maintain, and test Cover
  • Data structures the fun way: from binary search to quadtrees in 100 cups of coffee Cover
  • Pro TBB: C++ parallel programming with threading building blocks Cover
  • Think Java: how to think like a computer scientist Cover
  • Hands-on data structures and algorithms with Rust: learn programming techniques to build effective, maintainable, and readable code in Rust 2018 Cover
  • DATA STRUCTURES AND ALGORITHMS WITH THE C++ STL: A GUIDE FOR MODERN C++ PRACTITIONERS Cover
  • The self-taught computer scientist: the beginner's guide to data structures & algorithms Cover
  • Data structures using C Cover
  • Geometric Patterns with Creative Coding: Coding for the Arts Cover
  • JavaScript data structures and algorithms: an introduction to understanding and implementing core data structure and algorithm fundamentals Cover

Reviews from GoodReads

Loading GoodReads Reviews.

Citations

APA Citation, 7th Edition (style guide)

Vermeulen, A. F. (2018). Practical data science: a guide to building the technology stack for turning data lakes into business assets . Apress.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Vermeulen, Andreas François. 2018. Practical Data Science: A Guide to Building the Technology Stack for Turning Data Lakes Into Business Assets. [New York, New York]: Apress.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Vermeulen, Andreas François. Practical Data Science: A Guide to Building the Technology Stack for Turning Data Lakes Into Business Assets [New York, New York]: Apress, 2018.

Harvard Citation (style guide)

Vermeulen, A. F. (2018). Practical data science: a guide to building the technology stack for turning data lakes into business assets. [New York, New York]: Apress.

MLA Citation, 9th Edition (style guide)

Vermeulen, Andreas François. Practical Data Science: A Guide to Building the Technology Stack for Turning Data Lakes Into Business Assets Apress, 2018.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

Staff View

Grouped Work ID
1f20f5b5-c71d-1fe0-0ed2-ebf48e077b82-eng
Go To Grouped Work View in Staff Client

Grouping Information

Grouped Work ID1f20f5b5-c71d-1fe0-0ed2-ebf48e077b82-eng
Full titlepractical data science a guide to building the technology stack for turning data lakes into business assets
Authorvermeulen andreas françois
Grouping Categorybook
Last Update2025-01-24 12:33:29PM
Last Indexed2025-05-22 03:06:16AM

Book Cover Information

Image Sourcesyndetics
First LoadedAug 5, 2023
Last UsedFeb 22, 2025

Marc Record

First DetectedMar 21, 2023 11:45:32 AM
Last File Modification TimeMar 21, 2023 11:45:32 AM
SuppressedRecord had no items

MARC Record

LEADER03078cam a2200457 i 4500
001on1028639698
003OCoLC
00520230321114341.0
006m     o  d        
007cr unu||||||||
008180314s2018    nyua    o     001 0 eng d
020 |a 9781484230541
020 |a 148423054X
020 |a 1484230531
020 |a 9781484230534
035 |a (OCoLC)1028639698
037 |a CL0500000946|b Safari Books Online
040 |a UMI|b eng|e rda|e pn|c UMI|d STF|d TOH|d OCLCF|d CEF|d KSU|d OCLCQ|d DEBBG|d G3B|d S9I|d UAB|d VLY|d OCLCQ|d OCLCO|d OCLCQ
049 |a MAIN
050 4|a QA76.9.D35
08204|a 005.73|2 23
1001 |a Vermeulen, Andreas François,|e author.
24510|a Practical data science :|b a guide to building the technology stack for turning data lakes into business assets /|c Andreas François Vermeulen.
264 1|a [New York, New York] :|b Apress,|c [2018]
264 2|a New York, NY :|b Distributed to the Book trade worldwide by Springer Science + Business Media New York
264 4|c ©2018
300 |a 1 online resource (1 volume) :|b illustrations
336 |a text|b txt|2 rdacontent
337 |a computer|b c|2 rdamedia
338 |a online resource|b cr|2 rdacarrier
347 |a data file
500 |a Includes index.
5050 |a Chapter 1: Data Science Technology Stack -- Chapter 2: Vermeulen -- Krennwallner -- Hillman -- Clark -- Chapter 3: Layered Framework -- Chapter 4: Business Layer -- Chapter 5: Utility Layer -- Chapter 6: Three Management Layers -- Chapter 7: Retrieve Super Step -- Chapter 8: Assess Super Step -- Chapter 9: Process Super Step -- Chapter 10: Transform Super Step -- Chapter 11: Organize and Report Super Step --
520 |a 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. What You'll 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.
5880 |a Online resource; title from cover (viewed March 13, 2018).
590 |a O'Reilly|b O'Reilly Online Learning: Academic/Public Library Edition
650 0|a Data structures (Computer science)|9 35539
650 0|a Database management.|9 35533
85640|u https://library.access.arlingtonva.us/login?url=https://learning.oreilly.com/library/view/~/9781484230541/?ar|x O'Reilly|z eBook
994 |a 92|b VIA
999 |c 285946|d 285946