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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

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800561410
Length 260 pages
Edition 1st Edition
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Author (1):
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Bill Schmarzo Bill Schmarzo
Author Profile Icon Bill Schmarzo
Bill Schmarzo
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Table of Contents (14) Chapters Close

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

Transitioning from Business Insights to Business Optimization

Here are the actions to transition from Phase 2: Business Insights to Phase 3: Business Optimization:

  • Evaluate the customer, product, and operational Analytic Insights uncovered in the Business Insights phase for business and operational relevance based upon the Strategic, Actionable, and Material value of those insights with respect to the business and operational objectives of the top-priority use cases.
  • Develop Prescriptive and Preventative Analytics (preventative analytics are analytic outcomes that provide the analytic insights necessary to prevent an action or event from happening) in order to deliver actionable recommendations and propensity scores in support of the business and operational stakeholders' key Decisions with respect the top-priority business and operational Use Cases.
  • Deploy a Data Lake with full data management capabilities (indexing, cataloging, metadata enrichment, governance...
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