Principles of strategic data science creating value from data, big and small

Principles of Strategic Data Science describes a framework that creates value from data to help organizations meet their objectives. With this book, you'll bridge the gap between mathematics and computer science and also gain insight into the workings of the entire data science pipeline.

Bibliographic Details
Main Author: Prevos, Peter
Format: eBook
Language:English
Published: Birmingham, UK Packt Publishing Ltd., 2019.
Subjects:
Online Access:EBSCOhost
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100 1 |a Prevos, Peter,  |9 913202 
245 1 0 |a Principles of strategic data science  |b creating value from data, big and small  |c Peter Prevos. 
264 1 |a Birmingham, UK  |b Packt Publishing Ltd.,  |c 2019. 
300 |a 1 online resource (vi, 85 pages) 
505 8 |a Cover; FM; Table of Contents; Preface; Chapter 1: What is Data Science?; Introduction; Data-Driven Organization; The Data Revolution; The Elements of Data Science; Domain Knowledge; Mathematical Knowledge; Computer Science; The Unicorn Data Scientist?; The Purpose of Data Science; Chapter 2: Good Data Science; Introduction; A Data Science Trivium; Useful Data Science; Reality; Data; Information; Knowledge; The Feedback Loop; Sound Data Science; Validity; Reliability; Reproducibility; Governance; Aesthetic Data Science; Visualization; Reports; Best-Practice Data Science 
505 8 |a Chapter 3: Strategic Data ScienceIntroduction; The Data Science Continuum; Collecting Data; Descriptive Statistics; Business Reporting; Diagnostics; Qualitative Data Science; Predicting the Future; Traditional Predictive Methods; Machine Learning; Prescribing Action; Toward a Data-Driven Organization; Chapter 4: The Data-Driven Organization; Introduction; People; The Data Science Team; Data Science Consumers; Data Science Culture; Systems; Process; Define; Prepare; Understand; Communicate; The Limitations of Data Science; The Limits of Computation; Ethical Data Science; Chapter 5: References; Index. 
520 |a Principles of Strategic Data Science describes a framework that creates value from data to help organizations meet their objectives. With this book, you'll bridge the gap between mathematics and computer science and also gain insight into the workings of the entire data science pipeline. 
588 |a Description based on online resource; title from digital title page (viewed on August 25, 2020). 
653 0 |a Databases. 
653 0 |a Data mining. 
653 0 |a Big data. 
653 0 |a Electronic data processing. 
653 7 |a Big data.  |2 fast  |0 (OCoLC)fst01892965 
653 7 |a Data mining.  |2 fast  |0 (OCoLC)fst00887946 
653 7 |a Databases.  |2 fast  |0 (OCoLC)fst00888065 
653 7 |a Electronic data processing.  |2 fast  |0 (OCoLC)fst00906956 
655 0 |a EBSCO eBooks  |9 905790 
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856 |y Перейти в каталог НБ ТГУ  |u https://koha.lib.tsu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=1014149 
910 |a EBSCO eBooks 
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