Introduction
SAS migration has become a growing topic of interest recently. We’ve already discussed this subject in a few blogs by ProCogians, including myself and Brian Carter. Some key reasons for this shift include lower costs and codebases that are more flexible, versatile, and accessible with popular programming languages such as Python and R.
SAS is widely used in many industries, particularly those that are heavily regulated, like pharma and banking, which rely on SAS’s robust support, statistical reliability, and error-free security. Maintaining these standards requires significant investment in time and resources for rigorous testing and procedure development. SAS has dedicated teams to ensure that its procedures are fail-proof.
These factors contribute to why the time-to-market for SAS solutions is often delayed and why they struggle to keep pace with the latest technologies. This is somewhat disappointing for me, especially as a statistician, since SAS was one of the first programming languages I learned, and I have grown quite fond of it. However, the reality is that using open-source tools like Python pays off.
The shift from SAS to Python has become a strategic imperative for organizations across various industries. Python’s open-source nature, vast community support, and rich ecosystem of libraries have made it a compelling choice for data scientists and analysts. In this blog, we’ll outline some of the key benefits of this migration.
SAS to Python – Strategic Benefits
Cost Reduction: Python’s open-source nature eliminates the need for expensive SAS licenses, leading to significant cost savings.
Increased Accessibility: Python’s lower learning curve and widespread adoption make it easier to attract and retain talent.
Enhanced Collaboration: Python’s popularity and integration with other tools and platforms foster better collaboration within data teams and across the organization.
SAS to Python – Analytical Advantages
Rich Ecosystem of Libraries: Python offers numerous libraries for data manipulation, analysis, machine learning, and visualization, empowering data scientists to tackle complex problems efficiently. Moreover, its compatibility with cutting-edge Generative AI libraries enables users to apply these technologies to real-world applications easily.
Flexibility and Customization: Python’s flexibility allows for highly customized solutions, tailoring analysis to specific business needs.
Scalability: Python’s scalability enables handling large datasets and complex models, supporting the exponential growth of data available to organizations.
ProCogia: Your Partner in Migration
As organizations consider migrating from SAS to Python, it’s essential to have a strategic, well-defined roadmap and the necessary expertise. At ProCogia, we help organizations navigate this transition. With our deep understanding of both SAS and Python, we offer tailored migration services that meet your specific needs.
Laying the Groundwork for Migration: Our migration process begins with a comprehensive assessment of the organization’s analytical requirements, current systems, platforms, and servers. This assessment helps us lay the foundation for a seamless migration.
Centralizing SAS Code: Next, we organize the SAS code into a managed repository for version control and easy reference during the migration process.
The Migration Process: With the groundwork laid, our development team performs line-by-line translations of the SAS code. These translations can follow a direct conversion approach or involve complete redevelopment. Direct conversion improves code performance and readability, but it may introduce output differences. The optimal approach depends on the client’s specific requirements and timeline. Each translated code segment is stored in a repository for version control.
Output Evaluation & Unit Testing: After translating a SAS routine, we perform custom unit testing and code evaluation to ensure that all outputs align with the original expected results. Any discrepancies are analyzed and addressed, and we work closely with stakeholders to ensure a successful translation.
Training & Support in Python: We understand that not all teams may have experience with Python. Providing comprehensive training and support is fundamental to ensuring that all teams are comfortable using Python, creating a lasting and sustainable migration.
Conclusion
The journey from SAS to Python offers significant benefits. By embracing Python, organizations can reduce costs, attract top talent, and improve collaboration across teams. Ready to make the switch from SAS to Python? ProCogia’s expert data consulting team will manage the entire migration process, ensuring a seamless transition with minimal disruption. Let us help you unlock the full potential of Python for your business. Click here to learn more.
