Big Data: Understanding How Data Powers Big Business

For 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. Bill Schmarzo is the real deal. He shares his experience and know–how freely in a book that lays it out without hype." — Neil Raden, CEO & Principal Analyst, Hired Brains Research Big 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." — Marc Demarest, CEO and Principal, Noumenal, Inc. Bill 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." — John Furrier, Founder and CEO, SiliconANGLE Media, and co–host of @theCUBE Learn to leverage big data and boost business value Big 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. This 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: Leverage the Big Data Business Maturity Index to identify where and how big data can deliver meaningful business value Identify the "right" metrics against which to measure the success of your big data initiative Understand key big data technologies and advanced analytic developments Leverage 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 Summarize big data best practices, approaches, and value creation techniques into a Big Data Storymap to guide your organization

Preface xix Introduction xxi 1 The Big Data Business Opportunity 1 The Business Transformation Imperative 3 Walmart Case Study 3 The Big Data Business Model Maturity Index 5 Business Monitoring 7 Business Insights 7 Business Optimization 9 Data Monetization 10 Business Metamorphosis 12 Big Data Business Model Maturity Observations 16 Summary 18 2 Big Data History Lesson 19 Consumer Package Goods and Retail Industry Pre–1988 19 Lessons Learned and Applicability to Today′s Big Data Movement 23 Summary 24 3 Business Impact of Big Data 25 Big Data Impacts: The Questions Business Users Can Answer 26 Managing Using the Right Metrics 27 Data Monetization Opportunities 30 Digital Media Data Monetization Example 30 Digital Media Data Assets and Understanding Target Users 31 Data Monetization Transformations and Enrichments 32 Summary 34 4 Organizational Impact of Big Data 37 Data Analytics Lifecycle 40 Data Scientist Roles and Responsibilities 42 Discovery 43 Data Preparation 43 Model Planning 44 Model Building 44 Communicate Results 45 Operationalize 46 New Organizational Roles 46 User Experience Team 46 New Senior Management Roles 47 Liberating Organizational Creativity 49 Summary 51 5 Understanding Decision Theory 53 Business Intelligence Challenge 53 The Death of Why 55 Big Data User Interface Ramifi cations 56 The Human Challenge of Decision Making 58 Traps in Decision Making 58 What Can One Do? 62 Summary 63 6 Creating the Big Data Strategy 65 The Big Data Strategy Document 66 Customer Intimacy Example 67 Turning the Strategy Document into Action 69 Starbucks Big Data Strategy Document Example 70 San Francisco Giants Big Data Strategy Document Example 73 Summary 77 7 Understanding Your Value Creation Process 79 Understanding the Big Data Value Creation Drivers 81 Driver #1: Access to More Detailed Transactional Data 82 Driver #2: Access to Unstructured Data 82 Driver #3: Access to Low–latency (Real–Time) Data 83 Driver #4: Integration of Predictive Analytics 84 Big Data Envisioning Worksheet 85 Big Data Business Drivers: Predictive Maintenance Example 86 Big Data Business Drivers: Customer Satisfaction Example 87 Big Data Business Drivers: Customer Micro–segmentation Example 89 Michael Porter′s Valuation Creation Models 91 Michael Porter′s Five Forces Analysis 91 Michael Porter′s Value Chain Analysis 93 Value Creation Process: Merchandising Example 94 Summary 104 8 Big Data User Experience Ramifi cations 105 The Unintelligent User Experience 106 Understanding the Key Decisions to Build a Relevant User Experience 107 Using Big Data Analytics to Improve Customer Engagement 108 Uncovering and Leveraging Customer Insights 110 Rewiring Your Customer Lifecycle Management Processes 112 Using Customer Insights to Drive Business Profi tability 113 Big Data Can Power a New Customer Experience 116 B2C Example: Powering the Retail Customer Experience 116 B2B Example: Powering Small– and Medium–Sized Merchant Effectiveness 119 Summary 122 9 Identifying Big Data Use Cases 125 The Big Data Envisioning Process 126 Step 1: Research Business Initiatives 127 Step 2: Acquire and Analyze Your Data 129 Step 3: Ideation Workshop: Brainstorm New Ideas 132 Step 4: Ideation Workshop: Prioritize Big Data Use Cases 138 Step 5: Document Next Steps 139 The Prioritization Process 140 The Prioritization Matrix Process 142 Prioritization Matrix Traps 143 Using User Experience Mockups to Fuel the Envisioning Process 145 Summary 149 10 Solution Engineering 151 The Solution Engineering Process 151 Step 1: Understand How the Organization Makes Money 153 Step 2: Identify Your Organization’s Key Business Initiatives 155 Step 3: Brainstorm Big Data Business Impact 156 Step 4: Break Down the Business Initiative Into Use Cases 157 Step 5: Prove Out the Use Case 158 Step 6: Design and Implement the Big Data Solution 159 Solution Engineering Tomorrow’s Business Solutions 161 Customer Behavioral Analytics Example 162 Predictive Maintenance Example 163 Marketing Effectiveness Example 164 Fraud Reduction Example 166 Network Optimization Example 166 Reading an Annual Report 167 Financial Services Firm Example 168 Retail Example 169 Brokerage Firm Example 171 Summary 172 11 Big Data Architectural Ramifi cations 173 Big Data: Time for a New Data Architecture 173 Introducing Big Data Technologies 175 Apache Hadoop 176 Hadoop MapReduce 177 Apache Hive 178 Apache HBase 178 Pig 178 New Analytic Tools 179 New Analytic Algorithms 180 Bringing Big Data into the Traditional Data Warehouse World 181 Data Enrichment: Think ELT, Not ETL 181 Data Federation: Query is the New ETL 183 Data Modeling: Schema on Read 184 Hadoop: Next Gen Data Staging and Prep Area 185 MPP Architectures: Accelerate Your Data Warehouse 187 In–database Analytics: Bring the Analytics to the Data 188 Cloud Computing: Providing Big Data Computational Power 190 Summary 191 12 Launching Your Big Data Journey 193 Explosive Data Growth Drives Business Opportunities 194 Traditional Technologies and Approaches Are Insufficient 195 The Big Data Business Model Maturity Index 197 Driving Business and IT Stakeholder Collaboration 198 Operationalizing Big Data Insights 199 Big Data Powers the Value Creation Process 200 Summary 202 13 Call to Action 203 Identify Your Organization′s Key Business Initiatives 203 Start with Business and IT Stakeholder Collaboration 204 Formalize Your Envisioning Process 204 Leverage Mockups to Fuel the Creative Process 205 Understand Your Technology and Architectural Options 205 Build off Your Existing Internal Business Processes 206 Uncover New Monetization Opportunities 206 Understand the Organizational Ramifications 207 Index 209

Bill Schmarzo is the Chief Technology Officer for EMC Global Services' Enterprise Information Management & 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.