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)
10
Other Books You May Enjoy
11
Index
Appendix A: My Most Popular Economics of Data, Analytics, and Digital Transformation Infographics

EvD Theorem #2: Predictions, Not Data, Drive Value

It is the quantification of trends, patterns, and relationships that drive predictions about what is likely to happen.

It is the quantification of trends, patterns, and relationships around customers, products, services, operations, and markets that drive operational, management, and strategic predictions. And it is the value of these predictions (in support of the top-priority business and operational use cases) that ultimately determines the economic value of your data. And the best way to codify and ultimately monetize those trends, patterns, and relationships is through the use of Analytic Profiles.

As I discussed in Chapter 3, A Review of Basic Economic Concepts, Analytic Profiles or Digital Twins, provide a mechanism for capturing the metrics, predictive indicators, segments, scores, and business rules that codify the behaviors, preferences, propensities, inclinations, tendencies, interests, associations, and affiliations...