English | 2020 | ISBN: 1800561410 | 252 Pages | PDF, EPUB, MOBI | 37 MB
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
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.
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