Modernize Teradata Workloads Across Cloud Data Platforms

SAS2PY automates the end-to-end migration of legacy Informatica workflows— converting mappings, transformations, sessions, and workflow logic into scalable, cloud-native architectures optimized for performance, flexibility, and long-term sustainability.

Target Platforms and Outputs Include:

  • Cloud Data Warehouses: Snowflake, Google BigQuery, Amazon Redshift, Teradata Vantage, Apache Iceberg, Microsoft Fabric, Cloudera
  • Data Processing Frameworks: Python, PySpark, Snowpark, SQL, and native Databricks notebooks
  • Workflow Orchestration: DBT, Airflow, Git, Google Dataproc, Amazon EMR
  • Execution Capabilities: Visual pipeline execution across Databricks, Snowflake, and other platforms
  • Data Validation & Lineage: Schema mapping, partition-level data checks, metadata comparison, column-level validation, and full audit trails
  • Merlin AI (Optional): Built-in AI assistant for interactive code assistance, query optimization, and debugging—all on-prem or within your own secure cloud

SAS2PY preserves business logic and metadata, accelerates migration timelines, and provides full visibility from original Informatica workflows to optimized modern outputs—enabling a seamless, secure, and verifiable modernization of your enterprise data infrastructure.



See a Demo


Thumb





Validation & Testing for Informatica

  • Leverage advanced automation and optional Generative AI to analyze, validate, and optimize the migration of legacy Informatica workflows and transformation logic into modern platforms like Snowflake, Databricks, BigQuery, Redshift, Microsoft Fabric, and PySpark.

  • Data Validation: Automatically verify data accuracy by comparing row counts, column values, aggregates (sum, average), and schema structures between the original Informatica output and the converted target platform (e.g., Snowflake, Databricks, BigQuery, etc.).

  • Regression Testing: Perform side-by-side output comparisons between the original Informatica sessions and the migrated versions to ensure consistency in business rules and data transformation outcomes.

  • Error Handling & Remediation: Detect and resolve transformation errors, expression mismatches, mapping gaps, and logic inconsistencies during validation—before production deployment.

  • Partitioned Testing & Lineage Checks: Validate transformed data subsets (by date, region, etc.) and trace lineage across all stages of the migrated pipeline for auditability and compliance.

  • Optional AI Assistance (Merlin AI): Use built-in AI tools to identify anomalies, suggest query optimizations, and explain translation logic across Snowflake, Databricks, BigQuery, and other cloud platforms.

SAS2PY ensures your Informatica migration is not only fast—but also functionally accurate, fully auditable, and production-ready at enterprise scale.


Frequently Asked Questions

What is SAS2PY, and how does it simplify Informatica migration?

SAS2PY automates the conversion of legacy Informatica mappings, workflows, sessions, and transformation logic into Python, SQL, and modern cloud-native pipelines. It replaces months of manual re-engineering with a parser-driven, auditable process.

You can migrate up to 100,000 lines of Informatica logic in under 10 minutes, reducing migration timelines by up to 90% compared to manual refactoring.

Absolutely. SAS2PY scales across millions of lines of Informatica logic—including nested mappings, reusable transformations, parameterized sessions, and complex workflows—while preserving all dependencies.

We use row-by-row and aggregate-level validation, including schema mapping and output comparisons, to ensure 100% accuracy between your original Informatica logic and the converted results.

Yes. By transitioning from Informatica to open-source and cloud-native platforms, organizations typically save 50–75% on software licensing, infrastructure, and support costs.

SAS2PY performs schema matching, metadata comparison, column-level validations, and full regression tests to ensure that Informatica transformations are fully reproduced in the modern environment.