The Death of Data Science

It's coming. Better tooling and introspection has caused companies to increasingly question the effectiveness of Data Science efforts. As expectations continue to be unattainable and targets missed, this trend may accelerate. How did this happen? What should we do about it? Is there a future for Data Science and if so, what does it look like?

Transcript

1. The Death of Data Science Adam Drake CDO Summit Singapore 20160630 @aadrake http://aadrake.com https://sg.linkedin.com/in/aadrake
2. @aadrake #thoughtleader @aadrake #hacker
3. Background • Tech since the 90s • Variety of industries and countries • Business focus and tech passion • Advising
4. CEOs https://upload.wikimedia.org/wikipedia/commons/d/de/US_historical_energy_consumption.png
7. https://twitter.com/digHBS/status/624550100103245824
8. So it goes... • Cheaper storage/missing features in RDBMS • Hadoop/No(!)SQL • No(not only)SQL • Spark SQL • Postgres wins the Internet
9. 96 * 128GB = ~12TB
11. Data and Tech • Yahoo releases ~14TB of customer interaction data (JAN 2016) • Google releases Tensorflow (NOV 2015) • Amazon releases DSSTNE (Deep Scalable Sparse Tensor Network Engine) (MAY 2016)
12. Where's the value?
13. Leadership "...executives say senior-leader involvement and the right organizational structure are...even more important than its technical capabilities or tools." http://www.mckinsey.com/Business-Functions/Business-Technology/Our-Insights/The-need-to-lead-in-data-and-analytics
14. http://www.mckinsey.com/Business-Functions/Business-Technology/Our-Insights/The-need-to-lead-in-data-and-analytics
15. What to do? • Grow leadership capabilities • Build analytics, not Data Science • Get an overview of other areas (HR, Marketing, etc.) • Start positioning • Or wait...
16. Plot twist...
17. @aadrake http://aadrake.com https://sg.linkedin.com/in/aadrake