Big Data: Understanding How Data Powers Big Business
By: Bill Schmarzo (author)Paperback
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Leverage big data to add value to your business Social 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. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full 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.
* Shows how to decompose current business strategies in order to link big data initiatives to the organization s value creation processes * Explores different value creation processes and models * Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles * Provides methodology worksheets and exercises so readers can apply techniques * Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.
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.
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
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