Preface
1
A Higher Calling
2
The Difference Between a Good Data Scientist and a Great One
3
Learn the Business
4
Understand the Real Problem
5
Get Out There
6
Sorry, but You Can't Trust the Data
7
Make It Easy for People to Understand Your Insights
8
When the Data Leaves Off and Your Intuition Takes Over
9
Take Accountability for Results
10
What It Means to Be "Data‐driven"
11
Root Out Bias in Decision‐making
12
Teach, Teach, Teach
13
Evaluating Data Science Outputs More Formally
14
Educating Senior Leaders
15
Putting Data Science, and Data Scientists, in the Right Spots
16
Moving Up the Analytics Maturity Ladder
17
The Industrial Revolutions and Data Science
18
Epilogue
19
Appendix A: Skills of a Data Scientist
20
Appendix B: Data Defined
21
Appendix C: Questions to Help Evaluate the Outputs of Data Science
22
Appendix D: Ethical Considerations and Today's Data Scientist
23
Appendix E: Recent Technical Advances in Data Science
24
References
25
A List of Useful Links
26
Index
27
End User License Agreement