Creating a Data-Driven Organization: Practical Advice from the Trenches

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"O'Reilly Media, Inc.", Jul 23, 2015 - Business & Economics - 302 pages
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What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in across your company, from analysts and management to the C-Suite and the board.

Through interviews and examples from data scientists and analytics leaders in a variety of industries, author Carl Anderson explains the analytics value chain you need to adopt when building predictive business models—from data collection and analysis to the insights and leadership that drive concrete actions. You’ll learn what works and what doesn’t, and why creating a data-driven culture throughout your organization is essential.

  • Start from the bottom up: learn how to collect the right data the right way
  • Hire analysts with the right skills, and organize them into teams
  • Examine statistical and visualization tools, and fact-based story-telling methods
  • Collect and analyze data while respecting privacy and ethics
  • Understand how analysts and their managers can help spur a data-driven culture
  • Learn the importance of data leadership and C-level positions such as chief data officer and chief analytics officer
 

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Contents

Chapter 1 What Do We Mean by DataDriven?
1
Chapter 2 Data Quality
19
Chapter 3 Data Collection
41
Chapter 4 The Analyst Organization
59
Chapter 5 Data Analysis
83
Chapter 6 Metric Design
111
Chapter 7 Storytelling with Data
127
Chapter 8 AB Testing
155
Chapter 11 The DataDriven CSuite
217
Chapter 12 Privacy Ethics and Risk
237
Chapter 13 Conclusion
255
Further Reading
261
Why Is More Data Better?
263
Appendix B Vision Statement
271
Index
275
About the Author
284

Chapter 9 Decision Making
177
Chapter 10 DataDriven Culture
203

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About the author (2015)

Carl Anderson is the Director of Data Science at Warby Parker in New York overseeing data engineering, data science, supporting the broader analystics org, and creating a data-driven organization. He has had a broad-ranging career, mostly in scientific computing, covering areas such as healthcare modeling, data compression, robotics, and agent based modeling. He holds a Ph.D. in mathematical biology from the University of Sheffield, UK.