Book Image

The Economics of Data, Analytics, and Digital Transformation

By : Bill Schmarzo
5 (2)
Book Image

The Economics of Data, Analytics, and Digital Transformation

5 (2)
By: Bill Schmarzo

Overview of this book

In today’s digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization’s data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company’s operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization’s digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: "Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon."
Table of Contents (14 chapters)
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Appendix A: My Most Popular Economics of Data, Analytics, and Digital Transformation Infographics

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...