title: Big Data, Mining, and Analytics: Components of Strategic Decision Making
author:  Stephan Kudyba 
description: <P><EM>Kudyba again has put together an all-star cast in his new book focused on leveraging data, including the more traditional structured and also the unstructured incomprehensible source, to generate actionable information. This most current book provides a framework for both the advanced data jockeys to more analytically focused data-driven decision makers. A must-read for those wishing to be on the cutting edge of leveraging the multitude of data sources that businesses capture today.<BR></EM>Jeff Nicola,&nbsp;VP of Retail Sales at one of the nation's largest health insurance firms, and a Six Sigma Black Belt<BR><BR><EM>Dr. Kudyba has drawn upon his own, as well as industry experts, experiences to create a timely and thought provoking book on business intelligence.</EM> <STRONG>Big Data, Mining, and Analytics: Components of Strategic Decision Making</STRONG> <EM>should be recommended reading for both industry professionals and students involved in the challenge of developing actionable information. As described in this book, it is not a situation of the lack of data. It is, however, a situation where the plethora of amounts and types of data (whether structured or not) provides an arguably evolutionary situation, replete with new challenges, opportunities, and pitfalls. I highly recommend this book to anyone involved or interested in how big data, data mining, and analytics fit together in our current state; a state where the complexity, amount, and inadequate methodologies threaten the opportunities presented to leverage new sources of information to improve strategic as well as operational decision making.<BR></EM>Thad Perry, Ph.D., Director of Healthcare Informatics, Tennessee Technological University</P> <P></P> <P><EM>Just as early analytical competitors in the small data era moved out ahead of their competitors and built a sizable competitive edge, the time is now for firms to seize the big data opportunity. ... an excellent review of the opportunities involved in this revolution ... The road to the Big Data Emerald City is paved with many potholes. Reading this book can help you avoid many of them, and avoid surprise when your trip is still a bit bumpy.<BR></EM>From the Foreword by Thomas H. Davenport,<B> </B>Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics</P>
zlib_text: CHAPTER 1 
  Data and business 
  analytics 
  LEARNING OBJECTIVES 
  After studying this chapter, you should be able to: 
  1.1  explain how information produced from data informs business strategy 
  1.2  describe business analytics 
  1.3  explain basic statistical concepts 
  1.4  discuss the concept of ‘big data’ 
  1.5  explain the process of data mining. 
  Introduction 
  Every minute of the working day, people in businesses around the world make 
  decisions that determine whether the business will profit and grow, or stagnate and die. 
  Most of these decisions are made with the assistance of information about the 
  marketplace, economic and financial environments, workforce, competition and other 
  factors. Such information usually arises from the collection and analysis of data. 
  ‘Business analytics’ describes the tools through which data are collected, analysed, 
  summarised, interpreted and presented to facilitate the business decision-making 
  process. 
  In this text, we first examine how data and sta