The trends are clear. Open Source and code-intensive solutions are getting more and more popular for predictive analysis. It seems the trends will not decline, on the contrary, code will likely be the new de facto standard for the advanced analysis industry. Is this exclusively for the better? Do proprietary tools have any advantages? This talk will deal with pros and cons with different approaches for an efficient and robust data analysis and deployment.
Key Points:
- Pros and cons with Open Source
- Pros and cons with proprietary tools
- Reasoning around solutions to ensure efficient data analysis and efficiency in deployment
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