Rant: HOW is SAS so ubiquitous? Why has it persisted so long and why are companies so reluctant to remove their dependency on it? Was it really the only tool for analytics in the past?

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I'll add that, for certain industries, it's required. I know at least FDA and possibly DOJ and SEC require final submissions to be in .sas7bdat or .sd2 formats. So, kind of hard to do without running all your analysis in SAS.

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C1: it’s literally just the dataset, it doesn’t contain any code or additional analysis. .sas7bat files are not an “analysis language”, more like a data export format. You can do your analysis in whatever (python, R, etc), write it to a CSV, then import it into Sas and write it out as a sas7bat if you need that file format

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SAS provided the best analytics product, something usable in production, excellent support to clients, that’s how it built its share in the 2000s. It’s really sticky in many places because the production code is all written in it, e.g., banking, which means it’s a massive project with a ton of risk to move away. That’s why it so ubiquitous. It was the best and has enormous switching costs.

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If you were born a little earlier you would remember COBOL :). People asked the same questions

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I used SAS extensively in the past. I think it really was top dog for a enterprises for a while and now many places just use it enterprise wide, have lots of legacy code/programmers, and it would be difficult to switch easily.

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Thanks for all the responses so far. Insightful to realise SAS was perhaps the only fit-for-purpose solution at its time and became embedded and sticky. What baffles me is the lack on SAS'S part to modernise and try to catch up with the absolute TSUNAMI that's gonna hit them as people migrate to newer solutions. Perhaps they need some strategy consultants?

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My family member works for SAS and builds the architecture for compatibility. They are making packages compatible with Apache spark, cloud solutions, etc. they’re on top of it - I don’t think it’s really a tsunami. It’s going to be more piecemeal

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For areas such as pharmaceuticals and clinical trials, SAS is still dominant for a few reasons 1) dedicated support, if things go wrong, there is a sense of accountability, 2) SAS is numerically validated, there is a growing push for this with R, but the open source nature of the many libraries presents challenges - see this blog for details on the push https://www.2kmm.pl/blog/2KMM-s-blog-official-opening-and-our-participation-in--R-in-Pharma-2020--conference ; Python is significantly farther from away this goal than R, and will probably never get there due to the user focus on ML rather than stats 3) it is a legacy system and companies don’t like to change once they are entrenched

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Its the most redundant software in analytics. I've realized that companies claiming to move to R or Python are going to be very slow to get rid off SAS. The best thing to do is jump ship to a company that actually uses Python full fledged.

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Lol! It’s cos it works!

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