The Economics of Data, Analytics, and Digital Transformation

Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning

Key Features

Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset
Acquire implementable knowledge on digital transformation through 8 practical laws
Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly

Book DescriptionIn 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.”

What you will learn

Train your organization to transition from being data-driven to being value-driven
Navigate and master the big data business model maturity index
Learn a methodology for determining the economic value of your data and analytics
Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used
Become aware of digital transformation misconceptions and pitfalls
Create empowered and dynamic teams that fuel your organization’s digital transformation

Who this book is forThis book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.

Author Biography

Bill Schmarzo, the Dean of Big Data, is currently the Head of Customer Data Innovation at Dell Technologies. He is also a lecturer at Iowa State University and Coe College (Cedar Rapids, IA), 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 his course Big Data MBA and Thinking Like a Data Scientist. He has authored four books, written over 300 blogs for Data Science Central, appeared on podcasts, given numerous keynote presentations and university lectures, and is an active social media lightening rod on the topics of data science, AI, data economics, design thinking, and team empowerment.