Part 7/12:
The transition from enterprise tools like SAS and SPSS to open-source languages such as R and Python marked a pivotal moment, starting around 2009-2010. Open-source tools allowed broader access for students and professionals worldwide, fostering innovation and democratizing analytics.
This shift was driven by the availability of cutting-edge libraries, community support, and the reduction of licensing costs. As more talent learned and contributed openly, the ecosystem accelerated beyond the capabilities of traditional proprietary software, although certain industries—like clinical trials—continue to rely heavily on SAS due to regulatory and validation requirements.