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Comment by Fede_V | Hacker News Reader

Is this even a discussion? Anyone serious about analyzing data will use either R, Python (with Pandas/SciPy, etc), or Julia. For truly immense data sets that require pipelines, you'll use tools like spark, hadoop, etc - but SAS is basically a slightly improved excel.

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I'm an R person, but I used SAS in a past life, and I have to say, this is very wrong. SAS is nothing at all like an improved Excel in look, operation, or user-base. It can do much of what R can do (build forecast models, ML models, even OR models), but it just looks very different.

And the licensing model will make you pull your hair out. I ran into issues both with geography (not being allowed to use my license on a project in another country) and functionality (hey, that's a cool PROC...wait, I don't have the license to call it)

I think R and python will win the day, but it's not because SAS is anything like Excel. And there are a shit ton of "serious" data analysis people using SAS. They're just all in the enterprise. Every Fortune 500 company I've worked with used SAS except for one (who used R).

SAS put out a GUI front end which helps automate stuff for the SAS base program sometime ago, which may confuse people.

> SAS is basically a slightly improved excel.

SAS is a pretty big system, and I have worked with SAS for about 10 years, and I can't see any similarity with Excel at all. Which part of the SAS system do you think resembles Excel ? Here is a list of their products (http://support.sas.com/documentation/productaz/index.html)

Btw. I do think I am doing serious data analysis in a bank :-)

The only similarity I can think of is that everything is a table :).

He might have only seen Enterprise Guide, which indeed resembles Excel. But that a good thing, actually.

That's my guess. Personally, for 99% of my uses for SAS, all I see is the script window, the log, and the output window. That's about as far from 'Excel' as you can get while still having an interface.

Being a slightly improved Excel has significant advantages as well:

It's more accessible to people who are not coders but need to do statistics on real data, i.e. almost all researchers.

Although personally, I would use R/Python (the UI is more suited to me, and it's free, and I trust the results a little more, and I can read the code if I need to)... do you actually need anything more than SAS/SPSS provides? I doubt it.

The way in which SAS is like Excel is that everything is a table.

SAS is not very accessible, especially to non-coders.

Apologies, I haven't used SAS in so long that I had it confused slightly with SPSS.

I'd argue that SAS is much more accessible to non-coders than either R or Python, in that the SAS language is mostly an invocation of statistical procedures, rather than a full-on programming language.

From a field dominated by SAS, moving to R was a pretty steep transition, whereas when I approached R from having learned Python, things made a great deal more sense having been exposed to other programming languages.

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