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

The Economics of Artificial Intelligence

So, let me give you the key take-away lesson from this chapter right off the bat:

Using Artificial Intelligence (AI), you can create assets that appreciate in value (not depreciate), the more that these assets are used.

In this chapter, I will provide commercial proof points to that opening statement by examining Google's open-source strategy for accelerating the capabilities of the TensorFlow AI/Machine Learning (ML) framework, as well as Elon Musk's Tesla Fully Self-Driving (FSD) autonomous AI strategy for creating assets that appreciate in value through usage.

Yes, be prepared. If you're still struggling to grasp the unique economic potential of data assets—assets that never deplete, never wear out, and can be used across an unlimited number of use cases at close to zero marginal cost—then this chapter is going to blow your mind!

Let's start this exploration by revisiting a topic that was...