PRAISE FOR THE ANALYTICS LIFECYCLE TOOLKIT

"Full of wisdom and experience about analytics, this book's greatest strength is its lifecycle approach. From framing the question to getting results, you'll learn how analytics can really have an impact on organizations." --Thomas H. Davenport, Ph.D., Author of Competing on Analytics and Only Humans Need Apply

"This book condenses a lot of deep thinking on the wide field of analytics strategy. Analytics is not easy--there are no quickie AI/BI/ML shortcuts to understanding your data, your business, or your processes. You have to build a diverse team of talent. You have to respect the hazards of 'fishing expeditions' that may need false-discovery-rate adjustments. You should consider designed experiments to get the true behavior of a process, something that observational data may hint at, but not provide complete understanding. There are dimensions of data wrangling, feature engineering, and data sense-making that all call for different skills. But with deep investment in analytics comes deep insight into processes and tremendous opportunity for improvements. This book puts analytics in the context of a strategic business system, with all its dimensions." --John Sall, Ph.D., SAS co-founder and chief architect of JMP

"The Analytics Lifecycle Toolkit provides a clear prescription for organizations aiming to develop a high-performing and scalable analytics capability. Greg organizes and develops with unusual clarity some of the critical nontechnical aspects of the analytics value-chain, and links them with the technical as building blocks in a comprehensive practice. Studying this map of how to negotiate the challenges to effectiveness and efficiency in analytics could save organizations months, or even years of painful trial and error on the road to proficiency." --Scott Radcliffe, Executive Director, Data Analytics at Cox Communications

"Many books exist that answer the question 'what is the right tool to solve a problem?' This is one of the few books I've read that answers the much more difficult question 'how do we make analytics become transformative throughout our organization?' Incorporating elements of data science, design thinki