Open data science languages – Python and R – offer tremendous advantages over legacy and proprietary products. But how does your enterprise make this transition, crossing the line? How can you embrace R and Python, and their thousands of powerful analytic applications—without the accompanying legal risks?
Using open source technology can provide your data scientists and decisions makers with the analytical power they need to find and act on insights in real-time.
- Why open-source? When open-source is good vs. bad?
- How to go about open-source technologies?
- How to make sense of technologies – from Hadoop to Spark of the world?
- How to create open-source culture within the organization?5.How to democratize innovation through broad access to open data science tools
To access this webinar, please provide your contact information: