Migration away from SAS is becoming increasingly common among data-driven organizations. In this blog, you can read about the important considerations and how 227 Data can help ensure a smooth transition.
SAS migration increasingly becoming a topic of discussion
SAS has been a proven technology for data analysis, modeling, and reporting for many years. At the same time, we are seeing many organizations reevaluating the role of SAS. Some are choosing to switch partially or completely to open source solutions such as Python or R.
This is not an easy choice—and certainly not the only right one. Every migration brings advantages, but also risks and challenges. In this blog, we list the most common considerations and explain how 227 Data supports organizations with a possible migration.
Cost structure: open source can be more cost-effective
SAS is a powerful platform with associated licensing costs. Open source alternatives such as Python and R are available free of charge and are actively supported by large communities of data scientists and engineers. For organizations looking to optimize their data costs, this may be a reason to reevaluate the added value of SAS.
Please note that if you have specific requirements, such as ensuring compliance and auditability, the costs for additional tools can add up, which may reduce the advantage of open source.
Flexibility & innovation: open source evolves faster
Organizations want to experiment with machine learning, AI, and modern visualization tools such as Power BI or Tableau. In such cases, open source can often offer more possibilities in terms of integration and speed of innovation. This does not mean that SAS no longer has any value, but it does mean that it is important to regularly evaluate the future-proofing of your platform.
In addition, SAS offers advantages if you want to remain dependent on on-premise solutions, which can help you reduce your dependence on the US or other countries.
Legacy code and technical debt
One major obstacle we often see is that organizations sometimes still run on SAS code that was developed 15 to 20 years ago. This legacy can lead to enormous technical debt, making systems inflexible and stifling innovation. Teams then spend most of their time keeping old scripts running instead of innovating. This makes the overlap challenging, but at the same time necessary to make paralyzed processes future-proof again.
Availability of data talent
Most young data engineers and data scientists are trained in open source tools. SAS specialists are certainly still around, but the influx of new talent is mainly in Python and R. For organizations looking to expand their teams, this is often an important consideration.
Nevertheless, it is important to realize that a successful migration requires knowledge of SAS as well as open source tools and cloud technology to ensure a smooth transition.
Avoiding vendor lock-in
Many organizations strive to remain independent of a single supplier. When using SAS, there is a risk of vendor lock-in: you are bound by fixed licensing models, pricing structures, and the supplier's technological direction. In comparison, open source offers more freedom to flexibly combine tooling and cloud solutions to suit your own strategy and needs. At the same time, it is important to realize that vendor lock-in is not unique to SAS: dependencies can also arise with large cloud or data services from parties such as Google or Microsoft. Careful analysis of these risks – before you make any choices – is therefore essential.
Integration with modern data architectures
Cloud-native data platforms, data lakes, and modern ETL processes require flexibility. In some cases, integrating SAS with these environments can be more difficult. Migration can then help you remain scalable more quickly and easily. At the same time, SAS is still highly usable in many hybrid architectures—it depends on your specific situation.
How we help with SAS migration
At 227 Data, we regularly work with organizations that want to migrate (partially) from SAS to open source. We do this with experienced specialists—temporary or permanent—who can guide you through the entire process:
- Impact analysis and migration plan
- Rewriting SAS code to Python, R, or SQL
- Guidance with tooling implementation
- User training and adoption
- Knowledge and documentation assurance
A transition requires both vision and expertise. We ensure that you do not lose any knowledge and take the right steps.
Are you considering a (partial) migration?
We would be happy to discuss with you what this means for you in concrete terms, including the risks and opportunities. Schedule a no-obligation consultation with one of our advisors.
