Building a Data Driven Culture
summary
Argues that small data often beats Big Data, recommending observation studies and control samples over rushed instrumentation; cites 85% of data-driven insights fail and the Cobra example as a warning about gaming systems and unintended consequences. Recommends concrete KPIs (favoring continuous measures), Pareto charts, and a learning plan tied to customer needs. Names tools: Power BI, Tableau, Click View, Azure ML, Azure Data Factory and Excel’s stats add-on. Advises diverse teams—data PMs, data scientists, analysts and engineers—to peer-review for bias before shipping.
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chapters (25)
- 0:00Intro
- 0:30About me
- 1:10Data can be intimidating
- 2:19Reimagine and do things differently
- 3:07The law of unintended consequences
- 4:09The placebo effect
- 5:45Unconscious bias
- 7:01Diversity
- 7:58Data Skills
- 8:53Customer Empathy
- 10:23Different Situations
- 10:42Mayo Clinic
- 11:32Learning Plan
- 12:30KPIs
- 13:24attrition
- 13:56small data
- 14:23data literacy
- 15:29data visualization tools
- 15:54graphical analysis
- 17:00belief lifecycle
- 17:25scientific approach
- 18:06cheat sheet
- 18:29continuous normal data
- 19:05establishing urgency
- 20:13Dr King
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