So far we’ve conducted a simple linear regression in Excel, Python, R, Tableau and SAS. You can see that different tools can do similar things.
However when doing data analysis in general, what are the differences between these tools, other than the code, or the UI? Below is a comparison of the PROS and CONS of each tool.
| Tools | PROS | CONS |
| Excel | Easy to use, no coding required | Data size limitation – usually under 1 million records |
| Python | Can handle big data; open source, super popular | Need some coding |
| R | Can handle big data; open source, very popular | Need some coding |
| Tableau | Easy to use, can handle big data; great visualization, user interactive; no coding required | License can be expensive (unless using Tableau Public, which has limited features) |
| SAS | Can handle big data | Need some coding. License can be expensive (unless using SAS® OnDemand for Academics) |
You will make your judgement when adopting data analysis tools to solve business problems.
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