SAS to R & Python Migration Best Practices

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SAS to R & Python Migration Best Practices

At ProCogia, we specialize in guiding teams worldwide through the transition from legacy SAS systems to modern, open-source R and Python platforms. Our approach is client-centric, addressing the unique analytics requirements of each organization. This transition is more than just a technical shift; it involves a comprehensive assessment of existing analytic processes, followed by a tailored migration plan that adheres to industry best practices. These practices include utilizing version-controlled code repositories, establishing robust testing systems to ensure accurate migration, and optimizing R/Python processes for specific analytic needs, along with providing extensive staff training and support. Click here to read a use case on how we applied best practices in code conversion from SAS production processes to R for one of the largest market research companies in the world. Our experienced developers are adept at navigating the complexities of transitioning from SAS to R and Python. We recognize that shifting business analytics tools can initially pose challenges. However, our commitment lies in delivering a customized codebase that unlocks deeper data insights and enhances analytic capabilities for our clients.

The Process

The process starts with a detailed assessment of an organization’s analytic needs. We thoroughly evaluate current statistical and reporting routines, understanding the breadth of services offered by SAS, including data management, advanced statistical analysis, and business support. Our goal is to replicate these services efficiently in R and Python, tailoring requirements, and libraries to streamline processes.

End user focus

A critical aspect of our assessment is the end-user experience. The transition involves more than simply translating SAS code; it is about replicating processes to minimize disruptions. For instance, if SAS programmers frequently export reports to Excel, our R and Python solutions will ensure identical outputs.

IT Review & Organization

Furthermore, we review IT resources dedicated to SAS and propose R and Python-based alternatives, such as recommending an R server environment that mimics the benefits of SAS servers at a reduced cost and with enhanced capabilities. Organizing the code repository is another crucial step. We ensure all source code is managed within a version-controlled environment. Our developers can also create Shiny dashboards (for R) and similar interactive applications (for Python) to help clients monitor progress in large-scale migrations.

Testing & Evaluation

Unit testing and code evaluation in R and Python are tailored to each project. We aim to demonstrate that R and Python processes yield the same results as the original SAS procedures. Differences in results, often due to software idiosyncrasies or statistical method variations, are discussed with project owners to define a successful migration’s precision and accuracy. Directly translating SAS macros into R or Python often leads to inefficient code. Our teams focus on reproducing the results of source macros while leveraging the strengths of R and Python, ensuring maintainability and efficiency.

Training for the learning curve

Addressing the learning curve associated with R and Python is vital for a successful transition. We offer comprehensive training and support to ensure all users are comfortable with both languages, supplementing their knowledge with workshops and specialist sessions tailored to specific needs.

In Conclusion

migrating from SAS to R and Python involves a thoughtful, client-focused approach.  We have found that a thorough assessment of the source code and analytic environment, development of a thorough testing strategy, and ongoing training and communication with the end user, results in an efficient transition with minimal impact on business processes.

Let’s Connect @ PHUSE

Additionally, we’re excited to announce that we’ll be at PHUSE 2024. It’s a month out beginning on February 25th and we’d love to engage with you and talk about your projects. Visit us to explore how we can support your transition to R and Python, enhancing your data analytics capabilities. Let’s collaborate to unlock new opportunities in data analysis and insights. Find out more about the event here: Phuse 2024. We look forward to meeting you there!

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