Migration efforts measured in months instead of years.
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Cepheus's SAS migration offering addresses the core business problem of SAS migration – how do I move out FAST and RISK FREE. Our patent pending C2 toolchain and systemized processes help us convert 100% of the SAS code to open-source Python/PySpark, allowing you to focus on core business while we take care of the technology migration.
We are pioneers in Language Engineering - a specialized discipline that combines
deep technical expertise with business domain knowledge to translate analytical workflows
across platforms, languages, and technologies.
Unlike traditional code migration services that focus on syntax translation, we engineer
solutions that preserve and enhance your business logic - the actual analytical and
operational intelligence embedded in your code.
With 30+ years of experience delivering global technology solutions, our team including PhDs
have developed the world's first automated SAS migration toolchain which delivers >90%
conversion out of the box.
SAS is a fourth-generation, domain-specific language designed primarily for statistical
analysis and structured data manipulation.
It runs in a permissive execution environment. It tolerates errors, certain syntax
inconsistencies, and performs automatic type conversions where feasible. Much of the
underlying runtime behavior is abstracted from the developer.
Python and PySpark, by contrast, are third-generation, general-purpose technologies.
PySpark runs on a distributed Spark engine. Execution rules, typing behavior, and evaluation
semantics are explicit and strictly enforced because of its distributed architecture.
SAS executes programs sequentially. DATA steps process records row-by-row, and state is
implicitly retained between iterations. Ordering is often assumed, and many behaviors - such
as variable retention and type handling - are handled automatically.
PySpark executes transformations across a distributed cluster. Operations define a logical
execution plan that is partitioned and run in parallel. State is not implicitly preserved,
ordering is not guaranteed unless explicitly defined, and transformations are evaluated only
when triggered by an action.
These differences are not stylistic. Logic that relies on implicit state, sequential
execution, or assumed ordering in SAS must be made explicit in PySpark.
C2 SAS migration toolchain
Our migration methodology is fundamentally based on a complete
translation
approach. We migrate the entire SAS estates end to end, rather than relying on
partial conversions.
We use a proprietary, tool-driven framework that directly analyses SAS scripts
and determines all of the actual technical constructs found in the codebase,
such as macro functions and nested macro functions, data steps using RETAIN and
conditionals, etc.
Our semi-automated reconciliation framework helps in processing the large volume
of tables that need to be reconciled as part of a successful migration effort,
including but not limited to evaluating field-level transformation correctness,
automated regression testing and repeatability validation, and auto-generated
reconciliation reports. This level of validation is required to ensure the
correctness of downstream processes and reports.
As a result, our approach is one of the first of its kind to target close to
100% automated conversion, while ensuring functional accuracy and preservation
of the defined decimal precision, with minimal human in loop efforts required.
Our two-phase scoping approach ensures no surprises - an initial
quote followed
by detailed scoping, with clear prerequisites and deliverables at each phase,
utilizing industry-standard methodology and established algorithms for
complexity analysis and scoping.
The conversion toolchain relies only on standard pip libraries, and all
converted programs execute natively within the PySpark environment — no
proprietary runtime or additional dependencies required. Our toolchain is
deployed in a transparent, non-binary format, making it effortless to inspect,
deploy, and run. We also have containerized versions ready for deployment.
Our four-phase delivery process (Scoping → Conversion → Testing → Hypercare) has
delivered successful migrations across multiple industries.
Migration efforts measured in months instead of years.
No more hefty SAS licensing fees.
Predictable, repeatable outputs across environments.
Auto-generated reconciliation reports for every workflow.
Keep your A-team focused on business impact, instead of a multi-year migration.
Don’t just migrate your time-tested analytics - enhance them with AI-ready, scalable capabilities.
Ensure true ownership, not long-term consultant dependence.
Powered by a proprietary toolchain that analyses SAS code at the construct level — not the file level.
Complexity is measured against the actual technical DNA of your codebase, across macros, PROC steps, data steps, and their nested behaviors.
The granularity of our analysis is what makes accurate effort estimation possible — and what most vendors skip.
One of the first methodologies designed to target close to 100% automated conversion
Functional accuracy and decimal precision are preserved by design, not by exception
Minimal human-in-the-loop — by architecture, not by aspiration
Unlike most market players—who typically exclude complex or tightly coupled scripts from scope—we take full responsibility for migrating the entire SAS estates’, with a commitment to near-complete conversion accuracy.
"This depth of analysis fundamentally differentiates our SAS migration approach from the majority of service providers in the market. This one-of-a-kind methodology that ensures completeness, transparency, and operational readiness, while significantly minimizing post-migration rework and human involvement. This approach has enabled us to consistently deliver close to 100% accuracy and successful SAS migrations for our existing customers."
Contact us at info@cepheus.in for an initial quote.
