ISBN 9788126544691,Big Data Big Analytics: Emerging Business Intelligence and Analytic Trends for Todays Businesses

Big Data Big Analytics: Emerging Business Intelligence and Analytic Trends for Todays Businesses



Wiley India Pvt Ltd

Publication Year 2011

ISBN 9788126544691

ISBN-10 8126544694


Number of Pages 324 Pages
Language (English)


The simultaneous rise of cloud, social and mobile computing has created an explosion of new data. This explosion has rapidly overwhelmed the capacity of existing information systems, creating intense demand for new technologies designed to manage the flood of data created by businesses, consumers and automatic sensors. Thanks to the astonishingly fast growth of mobile social networking, much of the new data created is unstructured. Traditional methods for handling structured data are simply inadequate, inefficient and ineffective for managing the torrent of unstructured data generated by hundreds of millions of consumers and individuals worldwide. Was this product information helpful? Yes No TABLE OF CONTENTS 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 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 Consumers Have Changed - So Must Marketers The Right Approach: Cross Channel Lifecycle Marketing Social and Affiliate Marketing Empowering Marketing with Social Intelligence Fraud and Big Data Risk and Big Data Credit Risk Management Big Data and Algorithmic Trading Crunching Through Complex Interrelated Data Intraday Risk Analytics, a Constant Flow of Big Data Calculating Risk in Marketing Other Industries Benefit from Financial Services Risk Experience Big Data and Advances in Health Care 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 Donald Draper Reach, Resonance and Reaction The Need to Act Quickly Measurement Can Be Tricky Content Delivery Matters Too Optimization and Marketing Mixed Modeling Beard's Take on the Three Big Data vs in Advertising Using Consumer Products as a Doorway Big Data Technology The Elephant in the Room: Hadoop's Parallel World Old vs 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 Information Management The Big Data Foundation Big Data Computing Platforms Big Data Computation More on Big Data Storage Big Data Computational Limitations Big Data Emerging Technologies Business Analytics The Last Mile in Data Analysis Geospatial Intelligence Will Make Your Life Better 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° Modeling Need for Speed Let's Get Scrappy What Technology is Available? Moving from Beyond the Tools to Analytic Applications The People Part of the Equation Rise of the Data Scientist Learning Over Knowing Agility Scale and Convergence Multidisciplinary Talent Innovation Cost Effectiveness 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 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?