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The Economics of Data, Analytics, and Digital Transformation

You're reading from The Economics of Data, Analytics, and Digital Transformation The theorems, laws, and empowerments to guide your organization's digital transformation

Product type Paperback

Published in Nov 2020

Publisher Packt

ISBN-13 9781800561410

Length 260 pages

Edition 1st Edition

Concepts

Data Analysis

Author (1):

Bill Schmarzo

View More author details

Table of Contents (14) Chapters

Preface

1. The CEO Mandate: Become Value‑driven, Not Data-driven

2. Value Engineering: The Secret Sauce for Data Science Success FREE CHAPTER

3. A Review of Basic Economic Concepts

4. University of San Francisco Economic Value of Data Research Paper

5. The Economic Value of Data Theorems

6. The Economics of Artificial Intelligence

7. The Schmarzo Economic Digital Asset Valuation Theorem

8. The 8 Laws of Digital Transformation

9. Creating a Culture of Innovation Through Empowerment

10. Other Books You May Enjoy

11. Index

Appendix A: My Most Popular Economics of Data, Analytics, and Digital Transformation Infographics

1. Appendix B: The Economics of Data, Analytics, and Digital Transformation Cheat Sheet

Other Books You May Enjoy

If you enjoyed this book, you may be interested in this book by Packt:

Building Analytics Team

John K. Thompson

ISBN: 978-1-80020-316-7

Avoid organizational and technological pitfalls of moving from a defined project to a production environment
Enable team members to focus on higher-value work and tasks
Build Advanced Analytics and Artificial Intelligence (AA&AI) functions in an organization
Outsource certain projects to competent and capable third parties
Support the operational areas that intend to invest in business intelligence, descriptive statistics, and small-scale predictive analytics
Analyze the operational area, the processes, the data, and the organizational resistance

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Authors (1)

Bill Schmarzo

Bill Schmarzo

Bill Schmarzo, The Dean of Big Data is a University of San Francisco School of Management Executive Fellow and an Honorary Professor at the School of Business and Economics at the National University of Ireland-Galway where he teaches and mentors students in his courses “Big Data MBA” and “Thinking Like a Data Scientist". He is the author of Big Data: Understanding How Data Powers Big Business, Big Data MBA: Driving Business Strategies with Data Science, and The Art of Thinking Like a Data Scientist. He has written countless whitepapers, articles and blogs, and given keynote presentations and university lectures on the topics of data science, artificial intelligence/machine learning, data economics, design thinking and team empowerment.

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