We use SAS Enterprise Guide as a Business Intelligence/analytics tool at my work (Industrial Plant) - most of our production reporting is SAS based. We also use it for adhoc analysis/troubleshooting. I.e to spot long term declines in yield and that sort of thing.

Where SAS succeeds is they make it very easy for non programmers to do things like query databases extract, transform, merge data, create computed columns and output graphs and reports.

Enterprise Guide is 100% scriptable and has a programming language underneath it the "SAS langauge" basically anything you can do in the GUI has code that is generated in the backend which user can edit directly if they desire. In old versions of Enterprise Guide code the GUI generated tended to be pretty inefficient (especially the SQL side of things) so a lot of people hacked the code directly and bypassed the GUI - nowadays it has gotten pretty good not as much need to hand optimize things.

Best analogy I can give is Enterprise Guide is like Excel on steroids.

SAS also has very powerful statistical capabilities beyond what something like Excel offers. We leverage a lot of this stuff when we need to build engineering models, things like Time Series Analysis, Statistical Process Control, Linear and Non Linear Modelling (Including Stepwise and Logistic Regressions). There is even some Optimization solver type stuff I've used in past (though MATlab is more often used in my org for this work). SAS kind of takes the kitchen sink approach in R you need to install external packages from CRAN to unlock all this stuff in SAS tends to be "baked in". I've found if I read about a statistical technique in a paper good chance it is available in SAS - good example is a few years ago a grad student came to our plant and helped us perform some analysis using a technique called "Projection to Latent Structures" (PLS) to identify relationships between various factors on plant causing yield loss. At the time this wasn't very common - I think it is used in machine learning nowadays but SAS had a PLS procedure available for us to use (kind of like a function in other programming languages) and the documentation SAS provided was very good (especially for someone like me with engineering background rater than stats background).

The only other tool I know of that is remotely similar to Enterprise Guide is IBM's Cognos software and that is vastly more limited as far as the statistical modelling features are concerned.

My work is keen to try other software, in part due to license costs, I think. In the Last 6 months I've been on two training course for Microsoft Power BI, and Microsoft R-Open (which I think is just Open source R-Studio with some extra proprietary stuff thrown in).

I've now used both tools to do my day to day job. I managed to get by with each of them but I found usability fell short of ease of use of enterprise guide.

Power BI was nice and I think it has something to offer as far as data visualization but you need to do the actual modelling in some other language so doesn't really eliminate needs for SAS - more like compliments it.

R on the other hand is a lot lower level it has all the advanced statistics but you have to write the low level code yourself to unlock them which requires learning an entire programming language to build simple models. It will be a pretty hard sell getting Engineers (I'm talking mechanical, chemical engineers not software kind) and finance analyst people to use a tool like R.

I think R would hugely benefit from something like an "Enterprise Guide for R" - I.e a drag and drop GUI which generated R code for you.

Also I wouldn't say the SAS Languge itself is strictly an old-school legacy language (sure the origins of SAS are from the 70's and 80's and there is a lot of legacy cruft in the SAS programming language I'll give you that) - For me SAS is a little like C++ there is a heap of stuff that lives in the langauge for backwards compatibility with old programs but modern C++ program looks very different from early 90's C++ - same with SAS code.

I've found modern ODS graphics (SGplot, SGpannel, etc) was very much on par with "ggplot2" functionality in R which is what the training course covered for producing reports using R.

SAS to me is a bit like MATLAB (and hey we use both in Engineering world). Everyone hates this software and wants something better but nothing else approaches the usability of these tools so models continue to be built using them.