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Comment by jl6 | Hacker News Reader

SAS is also a huge iceberg, without much in the way of open source culture that lends itself to visibility. A lot of SAS happens behind closed doors at megacorps.

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Even some of the mega corps want to get away from SAS. A friend of mine who does data analytics at the power company told me they want to bring on more Python developers despite their regulators wanting things done in SAS.

Also notable that so many new shops are foregoing it entirely. SAS, and its price tag, is a holdover from the days when 'analytics' was an afterthought for companies looking to maximize profit.

Now that much less mature companies are realizing the value of 'analytics' (I hate that word) SAS's cost doesn't really make sense.

What word do you prefer to 'analytics', if we are talking about taking data and analysing it to extract insights?

This does not have to involve machine learning, and "pattern recognition" is an academic term (and might be confusing for laymen).

Definitely agreed. But the word analytics means too many different things to too many different people at this point. I'm in favor of more words to differentiate each part.

Different types of analysis:

- descriptive analysis (clustering, summary statistics, etc.)

- predictive analysis / forecasting

- optimization

- automation

I suppose that last one involves engineering as well.

We try to do this as much as possible where I work.

It's... kinda working.

Why not just "analysis"?

Business people seem determined to invent new jargon when our current vocabulary is sufficient.

The euphemism treadmill makes my raises bigger.

My company uses SAS extensively a large part of that is legacy (for the same reason we have a heap of Fortan code still). SAS has been in use here since the 80's. I have gone as far as porting some (non performance sensitive). C++ models into SAS because people in my org understand the language better.

I don't actually hate SAS and I'm very productive using it but at the same time I do feel that not knowing R limits my opportunities if I ever want to change jobs and work for an outside organisation.

We don't strictly use SAS for analytics. A big part of SAS we use is the "BI" side I don't know if that acronym is still in vogue but I'm talking about ad-hoc querying reporting etc. The kind of stuff one step above what you'd use a spreadsheet for if that makes sense.

I think where SAS excels is they have made it very easy for non experts to be productive with it. Kind of similar to MATLAB in engineering world if people are familiar with that.

A lot of non statiscians and non programmers use it inside my work (my background is engineering). Accountants, Managers, mechanical engineers etc are all pretty capable of using Enterprise Guide to run adhoc queries and generate reports and the like. The only other similar tool I'm aware of is IBM's Cognos. We used to use both packages (as well as Microsoft Access) but about 10 years ago the business agreed to standardize around SAS. I've heard there is a similar tool in the R world to Enterprise Guide (R-Studio I think???) but I'm not all that familiar with it I've heard it behaves more like an IDE rather then a drag and drop way to construct queries, graphs/reports etc.

If anyone has made the transition from SAS (or Cognos) to R (especially for a large org) I'd be keen to hear what tools you'd recommend and how the business found it?

Rstudio is an IDE. If you want a gui for R, check out Rattle.

My shop is going the opposite direction, from R/excel to SAS+Cognos. I'm not happy about that decision, but the pay is good and the problems are still interesting.

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