Predictive Analytics, Data Mining and Big Data
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Home > Business and Economics > Business and Management > Business strategy > Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and Methods(Business in the Digital Economy)
Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and Methods(Business in the Digital Economy)

Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and Methods(Business in the Digital Economy)


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About the Book

Predictive analytics, big data, and data mining are key topics for organizations who want to leverage the ever increasing amounts of data that organizations hold about their customers and other individuals. This easy to read, in-depth guide provides readers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, the pitfalls and dangers, and a contextual road map for developing solutions that deliver benefits to their organizations. This how-to-guide will help managers to make the most of these technologies in their business area.

Table of Contents:
1. Introduction 2. Using Predictive Models 3. Analytics, Organization and Culture 4. The Value of Data 5. Ethics and Legislation 6. Types of Predictive Models 7. The Predictive Analytics Process 8. How to Build a Predictive Model 9. Text Mining and Social Network Analysis 10. Hardware, Software and All That Jazz

About the Author :
Steven Finlay is one of the UK's leading experts on predictive analytics and its application within Big Data environments. He has extensive experience of developing predictive analytics solutions within Financial Services, Retailing, and Government organisations. Steven is currently Head of Analytics at HML, the UK's largest provider of mortgage administration services.

Review :
'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


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Product Details
  • ISBN-13: 9781137379283
  • Publisher: Palgrave Macmillan
  • Publisher Imprint: Palgrave MacMillan
  • Series Title: Business in the Digital Economy
  • ISBN-10: 1137379286
  • Publisher Date: 02 Jul 2014
  • Binding: Digital (delivered electronically)
  • Sub Title: Myths, Misconceptions and Methods


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