Includes bibliographical references and index.

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business.

Foreword Preface Acknowledgments Chapter 1 What Is Big Data and Why Is It Important? A Flood of Mythic "Start-up" Proportions Big Data is More Than Merely Big Why Now? A Convergence of Key Trends Relatively Speaking... A Wider Variety of Data The Expanding Universe of Unstructured Data Setting the Tone at the Top Notes Chapter 2 Industry Examples of Big Data Digital Marketing and the Non-line World Don't Abdicate Relationships Is IT Losing Control of Web Analytics? Database Marketers, Pioneers of Big Data Big Data and the New School of Marketing Fraud and Big Data Risk and Big Data Credit Risk Management Big Data and Algorithmic Trading Calculating Risk in Marketing Other Industries Benefit from Banking's Risk Experience Big Data and Advances in Healthcare "Disruptive Analytics" A Holistic Value Proposition BI is not Data Science Pioneering New Frontiers in Medicine Advertising and Big Data: From Papyrus to Seeing Somebody Big Data Feeds the Modern Day Draper Measurement Can Be Tricky Beard's Take on the Three Big Data V's in Advertising Using Consumer Products as a Doorway Notes Chapter 3 Big Data Technology The Elephant in the Room: Hadoop's Parallel World Old versus New Approaches Data Discovery: Work the Way People's Minds Work Open Source Technology for Big Data Analytics The Cloud and Big Data Predictive Analytics Moves into the Limelight Software as a Service BI Mobile Business Intelligence is Going Mainstream Ease of Mobile Application Deployment Crowdsourcing Analytics Inter and Trans Firewall Analytics R&D Approach Helps Adopt New Technology Adding Big Data Technology into the Mix Big Data Technology Terms Data Size 101 Notes Chapter 4 Information Management The Big Data Foundation Big Data Computing Platforms (or Computing Platforms that can handle the Big Data Analytics Tsunami) Big Data Computation More on Big Data Storage Big Data Computational Limitations Big Data Emerging Technologies Chapter 5 Business Analytics The Last Mile in Data Analysis Listening: Is it Signal or Noise? Consumption of Analytics From Creation to Consumption Visualizing: How to Make It Consumable? Organizations are using Data Visualization as a Way to Take Immediate Action Moving from Sampling to Using All the Data Thinking Outside the Box 360 Degree Modeling Need for Speed Let's Get Scrappy What Technology is Available? Moving from beyond the Tools to Analytic Applications Notes Chapter 6 The People Part of the Equation Rise of the Data Scientist Learning over Knowing Using Deep Math, Science and Computer Science The 90/10 Rule and Critical Thinking Analytic Talent and Executive Buy-in Developing Decision Sciences Talent Holistic View of Analytics Creating Talent for Decision Sciences Creating a Culture that Nurtures Decision Sciences Talent Setting up the Right Organizational Structure for Institutionalizing Analytics Chapter 7 Data Privacy and Ethics The Privacy Landscape The Great Data Grab Isn't New Preferences, Personalization, and Relationships Rights and Responsibility Playing in a Global Sandbox Conscientious and Conscious Responsibility Privacy May Be the Wrong Focus Can Data Be Anonymized? Balancing for Counter Intelligence Now What? Notes Conclusion Recommended Resources About the Authors Index.