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