Table of Contents
Preface vii
1 What Do We Mean by Data-Driven? 1
Data Collection 1
Data Access 2
Reporting 4
Alerting 5
From Reporting and Alerting to Analysis 6
Hallmarks of Data-Drivenness 9
Analytics Maturity 11
Overview 17
2 Data Quality 19
Facets of Data Quality 20
Dirty Data 22
Data Provenance 36
Data Quality Is a Shared Responsibility 38
3 Data Collection 41
Collect All the Things 41
Prioritizing Data Sources 44
Connecting the Dots 46
Data Collection 48
Purchasing Data 50
Data Retention 56
4 The Analyst Organization 59
Types of Analysts 59
Analytics Is a Team Sport 65
Skills and Qualities 69
Just One More Tool 71
5 Data Analysis 83
What Is Analysis? 84
Types of Analysis 86
6 Metric Design 111
Metric Design 112
Key Performance Indicators 119
7 Storytelling with Data 127
Storytelling 128
First Steps 131
Sell, Sell, Sell! 133
Data Visualization 134
Delivery 145
Summary 151
8 A/B Testing 155
Why A/B Test? 159
How To: Best Practices in A/B Testing 160
Other Approaches 171
Cultural Implications 174
9 Decision Making 177
How Are Decisions Made? 179
What Makes Decision Making Hard? 183
Solutions 193
Conclusion 200
10 Data-Driven Culture 203
Open, Trusting Culture 204
Broad Data Literacy 207
Goals-First Culture 209
Inquisitive, Questioning Culture 211
Iterative, Learning Culture 212
Anti-HiPPO Culture 214
Data Leadership 215
11 The Data-Driven C-Suite 217
Chief Data Officer 218
Chief Analytics Officer 228
Conclusion 234
12 Privacy, Ethics, and Risk 237
Respect Privacy 239
Practice Empathy 243
Data Quality 248
Security 249
Enforcement 251
Conclusions 252
13 Conclusion 255
Further Reading 263
Analytics Organizations 263
Data Analysis & Data Science 263
Decision Making 263
Data Visualization 264
A/B Testing 264
A On the Unreasonable Effectiveness of Data: Why Is More Data Better? 265
B Vision Statement 273
Index 277
