{"product_id":"big-data-big-analytics-isbn-9781118147603","title":"Big Data, Big Analytics","description":"\u003cp\u003e\u003cb\u003eUnique prospective on the big data analytics phenomenon for both business and IT professionals\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe 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. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability.\u003c\/p\u003e \u003cp\u003eThe Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eLearn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.)\u003c\/li\u003e \u003cli\u003eExplains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights\u003c\/li\u003e \u003cli\u003eExplores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eForeword xiii\u003c\/p\u003e \u003cp\u003ePreface xix\u003c\/p\u003e \u003cp\u003eAcknowledgments xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 What is Big Data and Why is It Important? 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA Flood of Mythic “Start-Up” Proportions 4\u003c\/p\u003e \u003cp\u003eBig Data is More Than Merely Big 5\u003c\/p\u003e \u003cp\u003eWhy Now? 6\u003c\/p\u003e \u003cp\u003eA Convergence of Key Trends 7\u003c\/p\u003e \u003cp\u003eRelatively Speaking . . . 9\u003c\/p\u003e \u003cp\u003eA Wider Variety of Data 10\u003c\/p\u003e \u003cp\u003eThe Expanding Universe of Unstructured Data 11\u003c\/p\u003e \u003cp\u003eSetting the Tone at the Top 15\u003c\/p\u003e \u003cp\u003eNotes 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Industry Examples of Big Data 19\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDigital Marketing and the Non-line World 19\u003c\/p\u003e \u003cp\u003eDon’t Abdicate Relationships 22\u003c\/p\u003e \u003cp\u003eIs IT Losing Control of Web Analytics? 23\u003c\/p\u003e \u003cp\u003eDatabase Marketers, Pioneers of Big Data 24\u003c\/p\u003e \u003cp\u003eBig Data and the New School of Marketing 27\u003c\/p\u003e \u003cp\u003eConsumers Have Changed. So Must Marketers. 28\u003c\/p\u003e \u003cp\u003eThe Right Approach: Cross-Channel Lifecycle Marketing 28\u003c\/p\u003e \u003cp\u003eSocial and Affiliate Marketing 30\u003c\/p\u003e \u003cp\u003eEmpowering Marketing with Social Intelligence 31\u003c\/p\u003e \u003cp\u003eFraud and Big Data 34\u003c\/p\u003e \u003cp\u003eRisk and Big Data 37\u003c\/p\u003e \u003cp\u003eCredit Risk Management 38\u003c\/p\u003e \u003cp\u003eBig Data and Algorithmic Trading 40\u003c\/p\u003e \u003cp\u003eCrunching Through Complex Interrelated Data 41\u003c\/p\u003e \u003cp\u003eIntraday Risk Analytics, a Constant Flow of Big Data 42\u003c\/p\u003e \u003cp\u003eCalculating Risk in Marketing 43\u003c\/p\u003e \u003cp\u003eOther Industries Benefit from Financial Services’ Risk Experience 43\u003c\/p\u003e \u003cp\u003eBig Data and Advances in Health Care 44\u003c\/p\u003e \u003cp\u003e“Disruptive Analytics” 46\u003c\/p\u003e \u003cp\u003eA Holistic Value Proposition 47\u003c\/p\u003e \u003cp\u003eBI is Not Data Science 49\u003c\/p\u003e \u003cp\u003ePioneering New Frontiers in Medicine 50\u003c\/p\u003e \u003cp\u003eAdvertising and Big Data: From Papyrus to Seeing Somebody 51\u003c\/p\u003e \u003cp\u003eBig Data Feeds the Modern-Day Donald Draper 52\u003c\/p\u003e \u003cp\u003eReach, Resonance, and Reaction 53\u003c\/p\u003e \u003cp\u003eThe Need to Act Quickly (Real-Time When Possible) 54\u003c\/p\u003e \u003cp\u003eMeasurement Can Be Tricky 55\u003c\/p\u003e \u003cp\u003eContent Delivery Matters Too 56\u003c\/p\u003e \u003cp\u003eOptimization and Marketing Mixed Modeling 56\u003c\/p\u003e \u003cp\u003eBeard’s Take on the Three Big Data Vs in Advertising 57\u003c\/p\u003e \u003cp\u003eUsing Consumer Products as a Doorway 58\u003c\/p\u003e \u003cp\u003eNotes 59\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Big Data Technology 61\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Elephant in the Room: Hadoop’s Parallel World 61\u003c\/p\u003e \u003cp\u003eOld vs. New Approaches 64\u003c\/p\u003e \u003cp\u003eData Discovery: Work the Way People’s Minds Work 65\u003c\/p\u003e \u003cp\u003eOpen-Source Technology for Big Data Analytics 67\u003c\/p\u003e \u003cp\u003eThe Cloud and Big Data 69\u003c\/p\u003e \u003cp\u003ePredictive Analytics Moves into the Limelight 70\u003c\/p\u003e \u003cp\u003eSoftware as a Service BI 72\u003c\/p\u003e \u003cp\u003eMobile Business Intelligence is Going Mainstream 73\u003c\/p\u003e \u003cp\u003eEase of Mobile Application Deployment 75\u003c\/p\u003e \u003cp\u003eCrowdsourcing Analytics 76\u003c\/p\u003e \u003cp\u003eInter- and Trans-Firewall Analytics 77\u003c\/p\u003e \u003cp\u003eR\u0026amp;D Approach Helps Adopt New Technology 80\u003c\/p\u003e \u003cp\u003eAdding Big Data Technology into the Mix 81\u003c\/p\u003e \u003cp\u003eBig Data Technology Terms 83\u003c\/p\u003e \u003cp\u003eData Size 101 86\u003c\/p\u003e \u003cp\u003eNotes 88\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Information Management 89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Big Data Foundation 89\u003c\/p\u003e \u003cp\u003eBig Data Computing Platforms (or Computing Platforms That Handle the Big Data Analytics Tsunami) 92\u003c\/p\u003e \u003cp\u003eBig Data Computation 93\u003c\/p\u003e \u003cp\u003eMore on Big Data Storage 96\u003c\/p\u003e \u003cp\u003eBig Data Computational Limitations 96\u003c\/p\u003e \u003cp\u003eBig Data Emerging Technologies 97\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Business Analytics 99\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Last Mile in Data Analysis 101\u003c\/p\u003e \u003cp\u003eGeospatial Intelligence Will Make Your Life Better 103\u003c\/p\u003e \u003cp\u003eListening: Is It Signal or Noise? 106\u003c\/p\u003e \u003cp\u003eConsumption of Analytics 108\u003c\/p\u003e \u003cp\u003eFrom Creation to Consumption 110\u003c\/p\u003e \u003cp\u003eVisualizing: How to Make It Consumable? 110\u003c\/p\u003e \u003cp\u003eOrganizations are Using Data Visualization as a Way to Take Immediate Action 116\u003c\/p\u003e \u003cp\u003eMoving from Sampling to Using All the Data 121\u003c\/p\u003e \u003cp\u003eThinking Outside the Box 122\u003c\/p\u003e \u003cp\u003e360° Modeling 122\u003c\/p\u003e \u003cp\u003eNeed for Speed 122\u003c\/p\u003e \u003cp\u003eLet’s Get Scrappy 123\u003c\/p\u003e \u003cp\u003eWhat Technology is Available? 124\u003c\/p\u003e \u003cp\u003eMoving from Beyond the Tools to Analytic Applications 125\u003c\/p\u003e \u003cp\u003eNotes 125\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 The People Part of the Equation 127\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eRise of the Data Scientist 128\u003c\/p\u003e \u003cp\u003eLearning over Knowing 130\u003c\/p\u003e \u003cp\u003eAgility 131\u003c\/p\u003e \u003cp\u003eScale and Convergence 131\u003c\/p\u003e \u003cp\u003eMultidisciplinary Talent 131\u003c\/p\u003e \u003cp\u003eInnovation 132\u003c\/p\u003e \u003cp\u003eCost Effectiveness 132\u003c\/p\u003e \u003cp\u003eUsing Deep Math, Science, and Computer Science 133\u003c\/p\u003e \u003cp\u003eThe 90\/10 Rule and Critical Thinking 136\u003c\/p\u003e \u003cp\u003eAnalytic Talent and Executive Buy-in 137\u003c\/p\u003e \u003cp\u003eDeveloping Decision Sciences Talent 139\u003c\/p\u003e \u003cp\u003eHolistic View of Analytics 140\u003c\/p\u003e \u003cp\u003eCreating Talent for Decision Sciences 142\u003c\/p\u003e \u003cp\u003eCreating a Culture That Nurtures Decision Sciences Talent 144\u003c\/p\u003e \u003cp\u003eSetting Up the Right Organizational Structure for Institutionalizing Analytics 146\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Data Privacy and Ethics 151\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Privacy Landscape 152\u003c\/p\u003e \u003cp\u003eThe Great Data Grab isn’t New 152\u003c\/p\u003e \u003cp\u003ePreferences, Personalization, and Relationships 153\u003c\/p\u003e \u003cp\u003eRights and Responsibility 154\u003c\/p\u003e \u003cp\u003ePlaying in a Global Sandbox 159\u003c\/p\u003e \u003cp\u003eConscientious and Conscious Responsibility 161\u003c\/p\u003e \u003cp\u003ePrivacy May Be the Wrong Focus 162\u003c\/p\u003e \u003cp\u003eCan Data Be Anonymized? 164\u003c\/p\u003e \u003cp\u003eBalancing for Counterintelligence 165\u003c\/p\u003e \u003cp\u003eNow What? 165\u003c\/p\u003e \u003cp\u003eNotes 167\u003c\/p\u003e \u003cp\u003eConclusion 169\u003c\/p\u003e \u003cp\u003eRecommended Resources 175\u003c\/p\u003e \u003cp\u003eAbout the Authors 177\u003c\/p\u003e \u003cp\u003eIndex 179\u003c\/p\u003e  \u003cp\u003eConsidered one of the top sales and marketing executives in the business analytics space, \u003cb\u003eMICHAEL MINELLI\u003c\/b\u003e is Vice President, Information Services, for MasterCard Advisors. The majority of his sixteen years of analytics industry experience was at SAS, where he spent over eleven years helping clients with large-scale analytic projects related to marketing, risk, supply chain, and finance. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMICHELE CHAMBERS\u003c\/b\u003e is currently in the Big Data Analytics startup world and was formerly the General Manager \u0026amp; Vice President of Big Data Analytics at IBM, where her team was responsible for working with customers to fully exploit the IBM Big Data Platform. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAMBIGA DHIRAJ\u003c\/b\u003e is the Head of Client Delivery for Mu Sigma, where she leads their delivery teams to solve high-impact business problems in the areas of marketing, supply chain, and risk analytics for market-leading companies across multiple verticals.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eBIG DATA BIG ANALYTICS\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eThe Age of Big Data Analytics is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. This represents a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability.  \u003c\/p\u003e\u003cp\u003eWritten for business managers and executives who want to make the most out of their information resources, \u003ci\u003eBig Data, Big Analytics\u003c\/i\u003e strikes a careful balance between high-level strategy and sample code, making an otherwise highly technical topic accessible through stories, metaphors, and analogies. The authors—decision science and analytics experts—describe the enabling technology and illustrate the value of Big Data through industry examples. After introducing the people and corporations who are successfully working with Big Data, the book delves deeper into the organization and the roles it takes to make Big Data successful. \u003c\/p\u003e\u003cp\u003eIn this user-friendly guide, you'll discover: \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cul\u003e \u003cli\u003eWhat Big Data is and why it's important\u003c\/li\u003e \u003cli\u003eIndustry examples (Financial Services, Healthcare, etc.)\u003c\/li\u003e \u003cli\u003eBig Data and the New School of Marketing\u003c\/li\u003e \u003cli\u003eFraud, risk, and Big Data\u003c\/li\u003e \u003cli\u003eBig Data technology\u003c\/li\u003e \u003cli\u003eOld versus new approaches\u003c\/li\u003e \u003cli\u003eOpen source technology for Big Data analytics\u003c\/li\u003e \u003cli\u003eThe Cloud and Big Data\u003c\/li\u003e \u003cli\u003ePredictive analytics\u003c\/li\u003e \u003cli\u003eCrowdsourcing analytics\u003c\/li\u003e \u003cli\u003eComputing platforms, limitations, and emerging technologies\u003c\/li\u003e \u003cli\u003eConsumption of analytics\u003c\/li\u003e \u003cli\u003eData visualization as a way to take immediate action\u003c\/li\u003e \u003cli\u003eMoving from beyond the tools to analytic applications\u003c\/li\u003e \u003cli\u003eCreating a culture that nurtures decision science talent\u003c\/li\u003e \u003cli\u003eA thorough summary of ethical and privacy issues\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThe availability of Big Data, low-cost commodity hardware, new information management, and analytic software has produced boundless opportunities for your organization to jump ahead of the competition. Discover how to analyze astonishing data sets quickly and cost-effectively with the tools and strategies found in \u003ci\u003eBig Data, Big Analytics\u003c\/i\u003e.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eBIG DATA BIG ANALYTICS\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eThe Age of Big Data Analytics is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. This represents a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability. \u003c\/p\u003e\u003cp\u003eWritten for business managers and executives who want to make the most out of their information resources, \u003ci\u003eBig Data, Big Analytics\u003c\/i\u003e strikes a careful balance between high-level strategy and sample code, making an otherwise highly technical topic accessible through stories, metaphors, and analogies. The authors—decision science and analytics experts—describe the enabling technology and illustrate the value of Big Data through industry examples. After introducing the people and corporations who are successfully working with Big Data, the book delves deeper into the organization and the roles it takes to make Big Data successful. \u003c\/p\u003e\u003cp\u003eIn this user-friendly guide, you'll discover: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eWhat Big Data is and why it's important\u003c\/li\u003e \u003cli\u003eIndustry examples (Financial Services, Healthcare, etc.)\u003c\/li\u003e \u003cli\u003eBig Data and the New School of Marketing\u003c\/li\u003e \u003cli\u003eFraud, risk, and Big Data\u003c\/li\u003e \u003cli\u003eBig Data technology\u003c\/li\u003e \u003cli\u003eOld versus new approaches\u003c\/li\u003e \u003cli\u003eOpen source technology for Big Data analytics\u003c\/li\u003e \u003cli\u003eThe Cloud and Big Data\u003c\/li\u003e \u003cli\u003ePredictive analytics\u003c\/li\u003e \u003cli\u003eCrowdsourcing analytics\u003c\/li\u003e \u003cli\u003eComputing platforms, limitations, and emerging technologies\u003c\/li\u003e \u003cli\u003eConsumption of analytics\u003c\/li\u003e \u003cli\u003eData visualization as a way to take immediate action\u003c\/li\u003e \u003cli\u003eMoving from beyond the tools to analytic applications\u003c\/li\u003e \u003cli\u003eCreating a culture that nurtures decision science talent\u003c\/li\u003e \u003cli\u003eA thorough summary of ethical and privacy issues\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThe availability of Big Data, low-cost commodity hardware, new information management, and analytic software has produced boundless opportunities for your organization to jump ahead of the competition. Discover how to analyze astonishing data sets quickly and cost-effectively with the tools and strategies found in \u003ci\u003eBig Data, Big Analytics.\u003c\/i\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988809564389,"sku":"NP9781118147603","price":52.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118147603.jpg?v=1761781677","url":"https:\/\/k12savings.com\/products\/big-data-big-analytics-isbn-9781118147603","provider":"K12savings","version":"1.0","type":"link"}