From rocks to a hammer when and how to change your company's analytical tools
summary
Company replaces SPSS/SAS (costly at $10k+ per year per license) with Python, IPython/Jupyter and a custom Plato library that automates repeated analytics, pulls from SQL and formats report-ready output. First attempt stalls on adoption; second builds a web GUI (Django/Ginga) with single-function pages, rolling rollout and training by feature. Results: automated workflows with near-zero manual errors, much faster turnaround, and license counts cut from ~20 to 2 remaining SPSS seats.
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chapters (10)
- 0:00Tool transition challenges
- 3:11Why change analytical tools
- 7:02Choosing Python
- 9:06First Python attempt
- 11:34Why first transition failed
- 15:49Lessons from initial approach
- 16:32Second attempt with web portal
- 20:46Key lessons from transition
- 23:56Future plans and benefits
- 24:17Q&A
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