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"Human Cloning: The Data Scientist Bottleneck Resolved" Dr. Alex Farquhar @ds_ldn
The document discusses a potential shortage of data scientists in the U.S. by 2018, estimating a need for 140,000 to 190,000 professionals. It suggests solutions including training more specialists, cross-training individuals, and leveraging automation and parallelization to manage the workload effectively. The emphasis is on simplifying tasks, using efficient tools, and improving processes for better productivity in data science.
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"Human Cloning: The Data Scientist Bottleneck Resolved" Dr. Alex Farquhar @ds_ldn
- 1. HUMAN CLONING The Data Scientist bottleneck resolved Dr Alex Farquhar Friday, 24 February 2012
- 2. exabytes data (IDC/EMCreport 2008) 20,000 15,000 10,000 5,000 0 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Friday, 24 February 2012
- 3. By 2018, theUnited States alone could face a shortage of 140,000 to 190,000 data people... Friday, 24 February 2012
- 4. WE’RE ALL DOOMED Friday,24 February 2012
- 5. DATA PEOPLE? © Drew Conway Friday, 24 February 2012
- 6. MAYBE WE CANJUST.... •1 statistician + 1 developer ≈ 1 data scientist? Friday, 24 February 2012
- 7. HOW ABOUT.... •4 statisticians + 4 developers ≈ 4 Data Scientists? Friday, 24 February 2012
- 8.
- 9.
- 10. WHAT CAN WEDO? • Train more new data scientists (not fast enough) • Cross-train people • Cobble together different skills in teams (see above) Friday, 24 February 2012
- 11. WHAT CAN WEDO? • Do more work Friday, 24 February 2012
- 12. DOING MORE • simplify (fob the work off) • automate (fob even more work off) • choose/build the right tools • parallelise • iterate Friday, 24 February 2012
- 13. SIMPLIFY & AUTOMATE • Counting stuff is not much fun Friday, 24 February 2012
- 14. SIMPLIFY & AUTOMATE Hive TSV files Hadoop Friday, 24 February 2012
- 15. AUTOMATE / PARALLELISE magic Hadoop Job Friday, 24 February 2012
- 16. AUTOMATE / PARALLELISE magic Hadoop Lots of jobs at once Job 1 Job 2 Job 3 Job 4 Friday, 24 February 2012
- 17. TOOLS • something thats allows fast iteration i.e. not java • R, ruby, python Friday, 24 February 2012
- 18.
- 19. ITERATE • try different things • improve what works • dump what doesn’t • constant improvement & learning → get faster Friday, 24 February 2012
- 20. WE’RE NOT ALL DOOMED Friday, 24 February 2012