Examining SAS: Shedding Light on the Programming Language’s Limitations
5 reasons why SAS poses challenges for programmers
SAS (Statistical Analysis System) is a programming language that has been widely used in the field of data analysis and statistical modeling for several decades. However, despite its popularity and longevity, SAS has its fair share of critics who argue that it is a horrible programming language. Here are five reasons why SAS poses challenges for programmers:
- Outdated Syntax: One of the major drawbacks of SAS is its outdated syntax. The language relies on cumbersome and verbose statements that make it time-consuming to read and write code. Compared to modern programming languages like R or Python, which offer concise and expressive syntax, SAS feels like a relic from the past. See the appendix section for an example of code in SAS to calculate age from birth date and perform a data summary.
- Limited Flexibility: SAS has a limited set of built-in functions and lacks the flexibility to integrate with other programming languages and tools. This restricts the possibilities for data manipulation and analysis to what is available in the base language or tools from the developer of SAS. In contrast, languages like R or Python have a vast ecosystem of libraries and frameworks that enable seamless integration with other tools and languages. Edit: There is some effort in recent years by the SAS Institute to expand open-source development capabilities (for example adding the ability to integrate Python code in SAS) but this still does not address the lack of a central software repository for SAS code like CRAN or PyPI which store packages.
- Costly Licensing: SAS is a commercial software, and obtaining a license can be quite expensive. This becomes a significant barrier for students, researchers, and small organizations who may not have the budget to invest in SAS. Open-source alternatives like R and Python, on the other hand, offer powerful data analysis capabilities at no cost.
- Steep Learning Curve: Learning SAS can be a daunting task, especially for beginners. The language has a steep learning curve, and its idiosyncrasies can be frustrating to grasp. Additionally, the SAS programming environment requires users to learn a specific set of procedures and commands, which limits their transferable skills to other programming languages.
- Lack of Community Support: While SAS has a sizable user base, its community support and resources are relatively limited compared to other programming languages. Finding help, tutorials, and code examples can be challenging, especially for niche or advanced topics. Unlike languages like Python and R, which have vibrant communities, SAS lacks a strong presence on popular platforms like Twitter, where users can engage in real-time discussions and share resources. Similarly, the availability of SAS-related blogs and online tutorials is scarce compared to the extensive libraries of content available for other languages. Additionally, while Stackoverflow does have some SAS-related questions and answers, the volume of discussions and community involvement is significantly lower compared to languages like Python or R. This limited community support hampers the learning experience and troubleshooting process for SAS programmers, making it a less favorable choice for those seeking an active and supportive programming community. Edit: SAS Communities and LexJansen’s website are the go-to resources for troubleshooting SAS code.
In conclusion, while SAS has been a dominant player in the field of data analysis, it has its fair share of shortcomings. Outdated syntax, limited flexibility, expensive licensing, steep learning curve, and lack of community support are some of the reasons why many consider SAS to be a horrible programming language. As the field of data analysis continues to evolve, more modern and flexible alternatives have emerged, providing users with better options for their analytical needs.
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