Introduction
Imagine a world where the daunting task of migrating vast batches of Base SAS code to R is no longer a monolithic, time-consuming endeavor. A world where analysts and data scientists can focus on deriving insights rather than grappling with syntax and structure. This vision is rapidly becoming reality with the help of Generative Artificial Intelligence. This is how we at ProCogia are leveraging new technologies to automate the code translation tasks.
The Motivation
SAS emerged as a prominent analytical tool in the early 2000s. Despite having a steeper learning curve, it offered a wider range of techniques and user-friendly options when compared to other choices at the time. Its reliability appealed to heavily regulated industries like banking and healthcare. However, open-source platforms like R and Python have recently been eclipsing SAS, providing superior capabilities, lower costs, and extensive community support. These tools are rapidly evolving along with the discoveries in Data Science and Computer Science, incorporating state-of-the-art techniques such as advanced computing and AI capabilities.
The desire for this efficiency, while maintaining code reliability, has been driving a migration from SAS to R in many industries. While complex, this transition offers numerous benefits. At ProCogia, we have helped our clients perform this migration in the most seamless and effective way possible, but this is an exhaustive task. We saw the immense potential of providing an automated solution to the task.
The Solution
To successfully navigate the Base SAS code to R code migration journey in an automated way, organizations need a robust and reliable translation tool. A solution that understands the nuances of both languages and accurately converts code. By leveraging advanced generative AI, our SAS to R Translator can quickly deliver these results.
We estimate that automated code translation can reduce migration time by around 90% compared to manual methods. This renders significant cost savings and accelerated time-to-value for organizations undertaking this transition. Moreover, our Translator App can improve code quality and consistency by adhering to established coding standards and best practices. By automating the mundane and error-prone aspects of manual code translation, your data teams can focus on higher-value activities such as data exploration, model development, and deployment. This shift in focus can lead to increased productivity, innovation, and competitive advantage.
While generative AI offers immense potential for automating code generation, it’s not without its challenges. Issues regarding the quality of the generated syntax and the lack of understanding of the original code can lead to many errors in the generated code. To address this concern, the app is implemented with several checks to ensure that the code is running as intended. If any error is found during the checks, it is passed as feedback to the underlying generative model with a request to fix the error. With this, the App ensures that the code produced is the best possible through many quality check iterations.
The app usage is very simple: The user is prompted to give a Base SAS code and possibly an example of the input and output data. With this, the App will translate the input code into R and will perform code and data quality checks to ensure that the generated code is working as intended. Just like that, in a matter of minutes and with just a mouse click, the user can have hundreds of lines of SAS converted into a tested R version.
Conclusion
Are you ready to embark on your SAS to R migration journey and reap the benefits of automated code translation? Schedule a consultation with us today to learn more about our SAS to R capabilities and discover how ProCogia can transform your data analytics processes.
If you’re attending the Posit::Conf (2024) in Seattle from August 12th-14th, visit our booth to chat about our innovative solutions. We look forward to connecting with you there!
