TY  - GEN
AU  - Schmarzo, Bill.
TI  - The economics of data, analytics, and digital transformation: the theorems, laws, and empowerments to guide your organization's digital transformation 
SN  - 9781800561410 (paperback)
U1  - 330.015195 
PY  - 2020///
CY  - Birmingham
PB  - Packt Publishing Ltd.
KW  - Data mining
KW  - Economic aspects
KW  - Big data
KW  - Data analytics
KW  - Artificial intelligence
KW  - Information technology
KW  - Business enterprises
KW  - Technological innovations
KW  - Econometrics
N1  - Includes bibliographical references and index; The CEO mandate: become value-driven, not data-driven -- Value engineering: the secret sauce for data science success -- A review of basic economic concepts -- University of San Francisco Economic Value of Data research paper -- The economic value of data theorems -- The economics of artificial intelligence -- The Schmarzo economic digital asset valuation theorem -- The 8 laws of digital transformation -- Creating a culture of innovation through empowerment -- My most popular economics of data, analytics, and digital transformation infographics -- The economics of data, analytics, and digital transformation cheat sheet -- Other books you may enjoy -- Index
N2  - The economics of data, analytics, and digital transformation: This book examines how organizations can move beyond simply collecting data and instead use data, analytics, artificial intelligence, and machine learning to create measurable economic and business value. Bill Schmarzo introduces frameworks for becoming value-driven, including the Big Data Business Model Maturity Index and value engineering, and explains economic concepts such as marginal costs, economic utility, and multiplier effects in the context of digital assets. The book explores the economic value of data, AI, and analytics, presents the Schmarzo Economic Digital Asset Valuation Theorem, and outlines eight laws for successful digital transformation. It also emphasizes innovation, employee empowerment, customer-focused decision-making, and the development of continuously learning organizations
ER  -