Data Science 2.0: From Outputs to Outcomes

on YouTube ↗45m

" summary

Argues that data is an economic asset and lays out a use-case, ROI-driven path from analytics outputs to measurable business outcomes: a value engineering framework, a big data strategy document mapping business initiatives to data and reuse, and stages of a data monetization roadmap. Introduces nano economics (analytic profiles/digital twins) to transform marginal returns, cites reuse of a point‑of‑sale dataset improving promotions ~2.5% and Tesla‑style continuous learning as examples, recommends mock‑ups, design thinking, and tools like TensorFlow and cloud/edge patterns.

AI-written summary · about

" chapters (10)

1. 0:00Intro
2. 0:40Vaccination
3. 4:17Data Science Evolution
4. 6:42How Effective Are You
5. 10:22Data is an Economic Asset
6. 13:46Nano Economics
7. 25:19Data Monetization
8. 33:23Value
9. 35:02QA
10. 43:25Outro

" related talks

• 36mAssuring Business Outcome Through AnalyticsPinky Sahu · Cypher 2017
• 13mEnterprise-Level Data Science SuccessPrabhakar Thanikasalam · rstudio::conf(2022)
• 23mValue in Data Science Beyond Models in ProductionEduardo Ariño de la Rubia · rstudio::conf 2019
• 51mFrom Data Confusion to Data IntelligenceElaine McVey, David Meza · posit::conf(2023)
• 24mData Science: the best path to align business objectivesEverton Gago · DevCamp 2019
• 44mPeople, Technology, Culture: How to make Data Science workMario Meir-Huber · Data Science Conference 4.0
• 16mRise of the Data ScientistKatrina Neal · Intelligent Content Conference 2017
• 21mIs It All About the Data?Cassie Kozyrkov, Ina Fried · DLD Munich 24