I did quite a bit of SAS programming in my work for over 20 years -- actually, from 1980 through 2001. In the early days, SAS was a mainframe-only product, but I liked it anyway. It's PL/I-like syntax resonated with me, then a PL/I programmer. In contrast to other statistical packages like SPSS and BMDP popular at the time, SAS was far more advanced in programming and data management capabilities, a critical differentiator pre SQL and data warehouse eras, when many analyses were one off, and linking disparate data sets was a big challenge. In the early 80's SAS made the strategically-critical decision to expand to mini and personal computers, in the process converting its code base from mainframe Assembler/Fortran/PL/I to the common C language so it could run on any platform. That investment paid off handsomely, catapulting SAS to the top of the statistical software market.

SAS continued fortifying its data management capabilities in the 80's and 90's, providing access to just about any type of file format, ASCII or EBCDIC, mainframe, mini or PC, and relational databases. It's introduction of a powerful SQL procedure further distanced SAS from competitors. With extensive programming language and function libraries, file and database access features, and data set handling capabilities, SAS could not only analyze your data, it could programmatically build your intelligence data stores as either SAS data sets or relational databases. I started using SAS more and more for data migration and reporting tasks, often in situations that had little to do with its statistical lineage.

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