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|a 1129152335
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|z (OCoLC)1129152335
|z (OCoLC)1132881399
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|a 4A0D7E0D-2E23-469B-9096-0910DE13928A
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|n http://www.overdrive.com
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|a HCDD
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| 100 |
1 |
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|a Kampakis, Stylianos,
|e author.
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| 245 |
1 |
4 |
|a The decision maker's handbook to data science :
|b a guide for non-technical executives, managers, and founders /
|c Stylianos Kampakis.
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| 250 |
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|a Second edition.
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| 264 |
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|a [Berkeley, CA] :
|b Apress,
|c [2020]
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| 264 |
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|c ©2020
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| 300 |
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|a 1 online resource (viii, 156 pages) :
|b illustrations
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
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| 504 |
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|a Includes bibliographical references and index.
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| 520 |
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|a Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don't realize is that data science is in fact quite multidisciplinary-useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker's Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker's Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will Learn Understand how data science can be used within your business. Recognize the differences between AI, machine learning, and statistics. Become skilled at thinking like a data scientist, without being one. Discover how to hire and manage data scientists. Comprehend how to build the right environment in order to make your organization data-driven. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.
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|a Online resource; title from title page (EBSCO, viewed February 18, 2020).
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|a Chapter 1: Demystifying Data Science and All the Other Buzzwords -- Chapter 2: Data Management -- Chapter 3: Data Collection Problems -- Chapter 4: How to Keep Data Tidy -- Chapter 5: Thinking like a Data Scientist (Without Being One) -- Chapter 6: A Short Introduction to Statistics -- Chapter 7: A Short Introduction to Machine Learning -- Chapter 8: Problem Solving -- Chapter 9: Pitfalls -- Chapter 10: Hiring and Managing Data Scientists -- Chapter 11: Building a Data-Science Culture -- Chapter 12: Epilogue: Data Science Rules the World -- Appendix A: Tools for Data Science.
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| 650 |
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|a Decision making
|x Data processing.
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| 650 |
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|a Big data.
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| 650 |
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|a Database management.
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| 650 |
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|a Big data
|2 fast
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|a Database management
|2 fast
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|a Decision making
|x Data processing
|2 fast
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| 758 |
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|i has work:
|a The decision maker's handbook to data science (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGdy6QDk4pFYyfxX9Ycfmd
|4 https://id.oclc.org/worldcat/ontology/hasWork
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| 776 |
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|i Print version:
|z 1484254937
|z 9781484254936
|w (OCoLC)1122454924
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| 856 |
4 |
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|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-1-4842-5494-3
|y Click for online access
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| 903 |
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|a SPRING-COMPUTING2020
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| 994 |
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|a 92
|b HCD
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