'A welcome addition to the literature on data driven decision making. Finlay's book gives a commendably non-technical discussion of the business issues associated with embedding analytics into an organisation and how data, big and small, can be used to support better decision making. It is peppered with case studies from the author's experience and is a great source of insight for technicians and business people alike.'
-Paul Russell, Director of Analytics, Experian UK&I
'A fully immersive introduction to the world of predictive analytics and its application to Big (and small) Data. Full of interesting stories and case studies, it provides a fascinating real world perspective of these technologies and how best to apply them. A must read for managers and data scientists alike.'
-Ioannis Stamatopoulos, Director for Moody's Enterprise Risk Solutions and Services, RiskMatrix
'Analytics is the latest organizational enthusiasm harnessing data, both internal and external, to add value is no easy task. This introduction hits all the right notes with case studies and insight gathered from Steve Finlay's considerable experience. The challenge which he meets is to explain in clear non-technical language the various methods and how they can be implemented; nor does he neglect the problems of embedding quantitative expertise into organizations that aren't used to its logic. Recommended for the manager or MBA student wanting an overview of this exciting new area.'
-Professor Robert Fildes, Distinguished Professor, Director, Lancaster Centre for Forecasting, Lancaster University, UK
'Mr Finlay has written a very readable, business friendly book that goes well beyond the formula. His real world experience and practical discussions would be of great benefit to industry practitioners.'
-Naeem Siddiqi, Global Product Manager, Banking Analytics Solutions, SAS Institute
If you want an excellent nontechnical overview of the predictive analytics process, this book should meet your needs... Finlay, a data scientist with decades of experience, provides an excellent introduction for readers, equipping them with the knowledge
to manage both the implementation and use of predictive analytics models in their organizations.
-Neil Desnoyers, Decision & System Sciences Department, Saint Joseph's University, Philadelphia, Pennsylvania: review in Interfaces, INFORMS