Most SAS folks that I have dealt think in terms of the language and how to do things easier or 'niftier' using traditional SAS. No issues there. What has intrigued me the most, though, over the past few years is to think in terms of the processes to write SAS code and whether those processes can be made easier. Also, whether the processes can be done outside of SAS and then incorporated. Well, why go out of SAS is the question. Well, oftentimes it is easier to build a GUI or to write an easy to maintain program in another language. For example, build a SAS program that reads in XML using XPath or loop through the process threads on a system looking for a file name. Well, not going to happen easily hence other languages and approaches are needed either before or after it gets into SAS.
On SAS-L today was a debate over macros vs whatever else or whether a user should learn macros early, late, never, sometime. I have nothing against macros but I do have an issue with the idea that SAS code generation is exclusively the domain of macros and SCL. I also don't think users should ever be held back on what they should or should not learn. No bounds in programming is my motto and the point of this blog entry.
Awhile back I wrote a program that was entirely in C# and just generated SAS format code. This provided the users with a great little graphical utility that generated valid format statements from various data sources (http://savian.net/utilities). Why? To do this in SAS would require Access engines, would not be graphically rich, and wouldn't allow the drag and drop stuff that I like.
This is where I think the SAS community can benefit: asking "how do I do this today and is there a better way?". I'm not saying it's right but that it provides an alternative view for how to accomplish a given task. The more we know the more we will embrace macros, embrace perl, embrace C#, embrace wild stuff like LINQ. The more you play, the more you will be able to help the end users.
Ok, I'm heading back to left field now...
This blog is designed to show various ways to use Data Virtualization, technologies, and SAS with Microsoft technologies with an eye toward outside of the box thinking.
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