With today’s updates, you’ll now be able to work with SQL, Python and R all on Sisense for Cloud Data Teams’s Unified Data Platform. Curious about which one you should choose for your workflow? Check out the chart below for details on the differences between each language and the capabilities they enable:

PythonR
A multi-purpose language
Loved by programmers and developers
Great for statistical data analysis and prototyping
Developed by statisticians for statisticians
Robust coding language built for flexibility with packages tailored to data Focused coding language built solely for statistics and data analysis
Relies on a few main libraries for data analysis, but has significantly more for other use cases Has thousands of packages tailored for specific use cases
Not as great for press-ready visualization Great for complex visuals with lots of easy customizations
Often used for machine learning, natural language processing, etc. Mostly used for complex statistical analysis
Integrates easily in a production workflow, and can be become an actual part of the product. Harder to integrate to a production workflow. Mostly a statistical analysis and graphic tool.

There are more and more similarities between the data analysis workflow in both. If all you’re doing is data analysis, it doesn’t really matter which one you use: SQL, Python, and R all work with Sisense for Cloud Data Teams.

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