{"product_id":"big-data-isbn-9781118739570","title":"Big Data","description":"\u003cp\u003e\u003cb\u003eLeverage big data to add value to your business\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSocial media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. \u003ci\u003eBig Data: Understanding How Data Powers Big Business\u003c\/i\u003e is a complete how-to guide to leveraging big data to drive business value.\u003c\/p\u003e \u003cp\u003eFull of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eShows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes\u003c\/li\u003e \u003cli\u003eExplores different value creation processes and models\u003c\/li\u003e \u003cli\u003eExplains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles\u003c\/li\u003e \u003cli\u003eProvides methodology worksheets and exercises so readers can apply techniques\u003c\/li\u003e \u003cli\u003eIncludes real-world examples from a variety of organizations leveraging big data\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eBig Data: Understanding How Data Powers Big Business\u003c\/i\u003e is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.\u003c\/p\u003e \u003cp\u003ePreface xix\u003c\/p\u003e \u003cp\u003eIntroduction xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 The Big Data Business Opportunity 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Business Transformation Imperative 3\u003c\/p\u003e \u003cp\u003eWalmart Case Study 3\u003c\/p\u003e \u003cp\u003eThe Big Data Business Model Maturity Index 5\u003c\/p\u003e \u003cp\u003eBusiness Monitoring 7\u003c\/p\u003e \u003cp\u003eBusiness Insights 7\u003c\/p\u003e \u003cp\u003eBusiness Optimization 9\u003c\/p\u003e \u003cp\u003eData Monetization 10\u003c\/p\u003e \u003cp\u003eBusiness Metamorphosis 12\u003c\/p\u003e \u003cp\u003eBig Data Business Model Maturity Observations 16\u003c\/p\u003e \u003cp\u003eSummary 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Big Data History Lesson 19\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eConsumer Package Goods and Retail Industry Pre-1988 19\u003c\/p\u003e \u003cp\u003eLessons Learned and Applicability to Today’s Big Data Movement 23\u003c\/p\u003e \u003cp\u003eSummary 24\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Business Impact of Big Data 25\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBig Data Impacts: The Questions Business Users Can Answer 26\u003c\/p\u003e \u003cp\u003eManaging Using the Right Metrics 27\u003c\/p\u003e \u003cp\u003eData Monetization Opportunities 30\u003c\/p\u003e \u003cp\u003eDigital Media Data Monetization Example 30\u003c\/p\u003e \u003cp\u003eDigital Media Data Assets and Understanding Target Users 31\u003c\/p\u003e \u003cp\u003eData Monetization Transformations and Enrichments 32\u003c\/p\u003e \u003cp\u003eSummary 34\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Organizational Impact of Big Data 37\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eData Analytics Lifecycle 40\u003c\/p\u003e \u003cp\u003eData Scientist Roles and Responsibilities 42\u003c\/p\u003e \u003cp\u003eDiscovery 43\u003c\/p\u003e \u003cp\u003eData Preparation 43\u003c\/p\u003e \u003cp\u003eModel Planning 44\u003c\/p\u003e \u003cp\u003eModel Building 44\u003c\/p\u003e \u003cp\u003eCommunicate Results 45\u003c\/p\u003e \u003cp\u003eOperationalize 46\u003c\/p\u003e \u003cp\u003eNew Organizational Roles 46\u003c\/p\u003e \u003cp\u003eUser Experience Team 46\u003c\/p\u003e \u003cp\u003eNew Senior Management Roles 47\u003c\/p\u003e \u003cp\u003eLiberating Organizational Creativity 49\u003c\/p\u003e \u003cp\u003eSummary 51\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Understanding Decision Theory 53\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBusiness Intelligence Challenge 53\u003c\/p\u003e \u003cp\u003eThe Death of Why 55\u003c\/p\u003e \u003cp\u003eBig Data User Interface Ramifications 56\u003c\/p\u003e \u003cp\u003eThe Human Challenge of Decision Making 58\u003c\/p\u003e \u003cp\u003eTraps in Decision Making 58\u003c\/p\u003e \u003cp\u003eWhat Can One Do? 62\u003c\/p\u003e \u003cp\u003eSummary 63\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Creating the Big Data Strategy 65\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Big Data Strategy Document 66\u003c\/p\u003e \u003cp\u003eCustomer Intimacy Example 67\u003c\/p\u003e \u003cp\u003eTurning the Strategy Document into Action 69\u003c\/p\u003e \u003cp\u003eStarbucks Big Data Strategy Document Example 70\u003c\/p\u003e \u003cp\u003eSan Francisco Giants Big Data Strategy Document Example 73\u003c\/p\u003e \u003cp\u003eSummary 77\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Understanding Your Value Creation Process 79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eUnderstanding the Big Data Value Creation Drivers 81\u003c\/p\u003e \u003cp\u003eDriver #1: Access to More Detailed Transactional Data 82\u003c\/p\u003e \u003cp\u003eDriver #2: Access to Unstructured Data 82\u003c\/p\u003e \u003cp\u003eDriver #3: Access to Low-latency (Real-Time) Data 83\u003c\/p\u003e \u003cp\u003eDriver #4: Integration of Predictive Analytics 84\u003c\/p\u003e \u003cp\u003eBig Data Envisioning Worksheet 85\u003c\/p\u003e \u003cp\u003eBig Data Business Drivers: Predictive Maintenance Example 86\u003c\/p\u003e \u003cp\u003eBig Data Business Drivers: Customer Satisfaction Example 87\u003c\/p\u003e \u003cp\u003eBig Data Business Drivers: Customer Micro-segmentation Example 89\u003c\/p\u003e \u003cp\u003eMichael Porter’s Valuation Creation Models 91\u003c\/p\u003e \u003cp\u003eMichael Porter’s Five Forces Analysis 91\u003c\/p\u003e \u003cp\u003eMichael Porter’s Value Chain Analysis 93\u003c\/p\u003e \u003cp\u003eValue Creation Process: Merchandising Example 94\u003c\/p\u003e \u003cp\u003eSummary 104\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Big Data User Experience Ramifications 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Unintelligent User Experience 106\u003c\/p\u003e \u003cp\u003eUnderstanding the Key Decisions to Build a Relevant User Experience 107\u003c\/p\u003e \u003cp\u003eUsing Big Data Analytics to Improve Customer Engagement 108\u003c\/p\u003e \u003cp\u003eUncovering and Leveraging Customer Insights 110\u003c\/p\u003e \u003cp\u003eRewiring Your Customer Lifecycle Management Processes 112\u003c\/p\u003e \u003cp\u003eUsing Customer Insights to Drive Business Profitability 113\u003c\/p\u003e \u003cp\u003eBig Data Can Power a New Customer Experience 116\u003c\/p\u003e \u003cp\u003eB2C Example: Powering the Retail Customer Experience 116\u003c\/p\u003e \u003cp\u003eB2B Example: Powering Small- and Medium-Sized Merchant Effectiveness 119\u003c\/p\u003e \u003cp\u003eSummary 122\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Identifying Big Data Use Cases 125\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Big Data Envisioning Process 126\u003c\/p\u003e \u003cp\u003eStep 1: Research Business Initiatives 127\u003c\/p\u003e \u003cp\u003eStep 2: Acquire and Analyze Your Data 129\u003c\/p\u003e \u003cp\u003eStep 3: Ideation Workshop: Brainstorm New Ideas 132\u003c\/p\u003e \u003cp\u003eStep 4: Ideation Workshop: Prioritize Big Data Use Cases 138\u003c\/p\u003e \u003cp\u003eStep 5: Document Next Steps 139\u003c\/p\u003e \u003cp\u003eThe Prioritization Process 140\u003c\/p\u003e \u003cp\u003eThe Prioritization Matrix Process 142\u003c\/p\u003e \u003cp\u003ePrioritization Matrix Traps 143\u003c\/p\u003e \u003cp\u003eUsing User Experience Mockups to Fuel the Envisioning Process 145\u003c\/p\u003e \u003cp\u003eSummary 149\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Solution Engineering 151\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Solution Engineering Process 151\u003c\/p\u003e \u003cp\u003eStep 1: Understand How the Organization Makes Money 153\u003c\/p\u003e \u003cp\u003eStep 2: Identify Your Organization’s Key Business Initiatives 155\u003c\/p\u003e \u003cp\u003eStep 3: Brainstorm Big Data Business Impact 156\u003c\/p\u003e \u003cp\u003eStep 4: Break Down the Business Initiative into Use Cases 157\u003c\/p\u003e \u003cp\u003eStep 5: Prove Out the Use Case 158\u003c\/p\u003e \u003cp\u003eStep 6: Design and Implement the Big Data Solution. 159\u003c\/p\u003e \u003cp\u003eSolution Engineering Tomorrow’s Business Solutions 161\u003c\/p\u003e \u003cp\u003eCustomer Behavioral Analytics Example 162\u003c\/p\u003e \u003cp\u003ePredictive Maintenance Example 163\u003c\/p\u003e \u003cp\u003eMarketing Effectiveness Example 164\u003c\/p\u003e \u003cp\u003eFraud Reduction Example 166\u003c\/p\u003e \u003cp\u003eNetwork Optimization Example 166\u003c\/p\u003e \u003cp\u003eReading an Annual Report 167\u003c\/p\u003e \u003cp\u003eFinancial Services Firm Example 168\u003c\/p\u003e \u003cp\u003eRetail Example 169\u003c\/p\u003e \u003cp\u003eBrokerage Firm Example 171\u003c\/p\u003e \u003cp\u003eSummary 172\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Big Data Architectural Ramifications 173\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBig Data: Time for a New Data Architecture 173\u003c\/p\u003e \u003cp\u003eIntroducing Big Data Technologies 175\u003c\/p\u003e \u003cp\u003eApache Hadoop 176\u003c\/p\u003e \u003cp\u003eHadoop MapReduce 177\u003c\/p\u003e \u003cp\u003eApache Hive 178\u003c\/p\u003e \u003cp\u003eApache HBase 178\u003c\/p\u003e \u003cp\u003ePig 178\u003c\/p\u003e \u003cp\u003eNew Analytic Tools 179\u003c\/p\u003e \u003cp\u003eNew Analytic Algorithms 180\u003c\/p\u003e \u003cp\u003eBringing Big Data into the Traditional Data Warehouse World 181\u003c\/p\u003e \u003cp\u003eData Enrichment: Think ELT, Not ETL 181\u003c\/p\u003e \u003cp\u003eData Federation: Query is the New ETL 183\u003c\/p\u003e \u003cp\u003eData Modeling: Schema on Read 184\u003c\/p\u003e \u003cp\u003eHadoop: Next Gen Data Staging and Prep Area 185\u003c\/p\u003e \u003cp\u003eMPP Architectures: Accelerate Your Data Warehouse 187\u003c\/p\u003e \u003cp\u003eIn-database Analytics: Bring the Analytics to the Data 188\u003c\/p\u003e \u003cp\u003eCloud Computing: Providing Big Data Computational Power 190\u003c\/p\u003e \u003cp\u003eSummary 191\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Launching Your Big Data Journey 193\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eExplosive Data Growth Drives Business Opportunities 194\u003c\/p\u003e \u003cp\u003eTraditional Technologies and Approaches Are Insufficient 195\u003c\/p\u003e \u003cp\u003eThe Big Data Business Model Maturity Index 197\u003c\/p\u003e \u003cp\u003eDriving Business and IT Stakeholder Collaboration 198\u003c\/p\u003e \u003cp\u003eOperationalizing Big Data Insights 199\u003c\/p\u003e \u003cp\u003eBig Data Powers the Value Creation Process 200\u003c\/p\u003e \u003cp\u003eSummary 202\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Call to Action 203\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIdentify Your Organization’s Key Business Initiatives 203\u003c\/p\u003e \u003cp\u003eStart with Business and IT Stakeholder Collaboration 204\u003c\/p\u003e \u003cp\u003eFormalize Your Envisioning Process 204\u003c\/p\u003e \u003cp\u003eLeverage Mockups to Fuel the Creative Process 205\u003c\/p\u003e \u003cp\u003eUnderstand Your Technology and Architectural Options 205\u003c\/p\u003e \u003cp\u003eBuild off Your Existing Internal Business Processes 206\u003c\/p\u003e \u003cp\u003eUncover New Monetization Opportunities 206\u003c\/p\u003e \u003cp\u003eUnderstand the Organizational Ramifications 207\u003c\/p\u003e \u003cp\u003eIndex 209\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eBill Schmarzo\u003c\/b\u003e is the Chief Technology Officer for EMC Global Services' Enterprise Information Management \u0026amp; Analytics service line. Nicknamed the Dean of Big Data, he is responsible for setting strategy for EMC's big data consulting business. He created the Business Benefits Analysis methodology and has served on the faculty of The Data Warehouse Institute.\u003c\/p\u003e  \u003cp\u003eFor decades, all of the technologies that organizations used to measure and forecast their operations were a small niche in enterprise computing. That situation reversed itself a few years ago, and now the inevitable emergence of big data demands clear thinking and advice.\u003c\/p\u003e \u003cp\u003eBill Schmarzo is the real deal. He shares his experience and know-how freely in a book that lays it out without hype.\"\u003cbr\u003e —\u003cb\u003eNeil Raden,\u003c\/b\u003e CEO \u0026amp; Principal Analyst, Hired Brains Research\u003c\/p\u003e \u003cp\u003eBig Data offers good sense, practical guidance, and pragmatism in what is at present a confused, confusing, and overly theoretical area. Anyone venturing into the big data outback would do well to stick Bill's book in their backpack.\"\u003cbr\u003e —\u003cb\u003eMarc Demarest,\u003c\/b\u003e CEO and Principal, Noumenal, Inc.\u003c\/p\u003e \u003cp\u003eBill is a leading voice in big data technology and the impact to business, and is referred to in the industry as 'the Dean of Big Data.' If you want the straight scoop on how and what to do with big data, read Bill's book.\"\u003cbr\u003e —\u003cb\u003eJohn Furrier,\u003c\/b\u003e Founder and CEO, SiliconANGLE Media, and co-host of @theCUBE\u003c\/p\u003e \u003cp\u003e\u003cb\u003eLearn to leverage big data and boost business value\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBig data is more than another hot technology trend. In fact, it's as much about business transformation as about technology. It's about leveraging the unique, actionable insights gleaned about your customers, products, and operations to rewire your value creation process and optimize your key business initiatives. Big data is about making money.\u003c\/p\u003e \u003cp\u003eThis book tackles big data business opportunities head-on. You'll find practical advice, techniques, methodologies, downloadable worksheets, and many examples gained from years of working with some of the world's leading analytics-driven organizations. You'll learn to:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eLeverage the Big Data Business Maturity Index to identify where and how big data can deliver meaningful business value\u003c\/li\u003e \u003cli\u003eIdentify the \"right\" metrics against which to measure the success of your big data initiative\u003c\/li\u003e \u003cli\u003eUnderstand key big data technologies and advanced analytic developments\u003c\/li\u003e \u003cli\u003eLeverage industry standard value creation models such as Michael Porter's Five Forces and Value Chain to identify how the big data business drivers can impact your organization's key business processes\u003c\/li\u003e \u003cli\u003eSummarize big data best practices, approaches, and value creation techniques into a Big Data Storymap to guide your organization\u003c\/li\u003e \u003c\/ul\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988810580197,"sku":"NP9781118739570","price":39.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118739570.jpg?v=1761781680","url":"https:\/\/k12savings.com\/es\/products\/big-data-isbn-9781118739570","provider":"K12savings","version":"1.0","type":"link"}