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The Economics of Data, Analytics, and Digital Transformation

You're reading from The Economics of Data, Analytics, and Digital Transformation

Product type Book

Published in Nov 2020

Publisher Packt

ISBN-13 9781800561410

Pages 260 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Bill Schmarzo

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

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

University of San Francisco Economic Value of Data Research Paper

DEAN OF BIG DATA TIP:

Note: This chapter is a republishing of the original ground-breaking research paper titled "Applying Economic Concepts to Big Data to Determine the Financial Value of the Organization's Data and Analytics and Understanding the Ramifications on the Organizations' Financial Statements and IT Operations and Business Strategies" that Professor Mouwafac Sidaoui and I did while at the University of San Francisco School of Management.

I am including the paper in its original version (except for some minor changes) because the research process and subsequent discoveries provided the catalyst for writing this book.

This paper truly caused me to change my frame with respect to how I thought about determining the value of data, and ultimately, the value of analytics.

I hope you enjoy reading—and studying—it as much as I enjoyed researching and...

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Authors (1)

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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