Effortlessly convert your SAS scripts, macros, data steps, and SQL queries. Reduce migration timelines from months to weeks while maintaining code accuracy and functionality.
Upload legacy Code
Automated Analysis & Conversion
GenAI: Execute & Reconcile
Reduce migration timelines from months to weeks while maintaining code accuracy and functionality.
Gain end-to-end visibility into your migration journey with detailed lineage tracking, ensuring complete transparency.
Simplify and operationalize migrations using integrations with DBT, Informatica, and other modern deployment tools.
Static code analysis and data lineage of all code including SQLs
PEP257 compliant self documentation for all generated code
Leverage cutting-edge generative AI to analyze, optimize, and validate the converted SAS code into an optimized solution.
Reduce SAS licensing, leverage cutting edge technology.
Experience 10x faster conversion rates with SAS2PY.
Achieve a remarkable +95% automation, saving time & money.
Enhance the capabilities of your current data scientists for the new wave of AI,
primarily driven by Python technologies.
It is a breeze with our built-in support for all 3 public cloud platforms as well as Databricks, Snowflake and other platforms.
Empower your team with access to advanced technology to elevate your product and exceed customer expectations.
Enhance scalability and performance by transitioning your data transformation operations to PySpark, enabling seamless handling of petabyte-scale datasets, and leverage Scikit-Learn or TensorFlow for advanced machine learning models, integrated with SageMaker for streamlined deployment and superior analytics.
Elevate your data analytics and machine learning capabilities by adopting
PySpark
for data transformation, effortlessly managing petabyte-scale datasets, while
harnessing the power of Scikit-Learn or TensorFlow models, seamlessly integrated
with Azure ML for cutting-edge insights and streamlined deployment.
Maximize your data processing and machine learning potential by migrating data
transformation workflows to PySpark, ensuring scalability for petabyte-scale
data,
and adopting Scikit-Learn or TensorFlow for robust machine learning models,
perfectly integrated with Google AI Platform for enhanced efficiency and
innovative
analytics.
