SAS to Microsoft Fabric Automated Migration | 75% Guaranteed Automation

Organizations running large-scale analytics on SAS are increasingly modernizing their data platforms to Microsoft Fabric to improve scalability, reduce infrastructure cost, and enable cloud-native analytics and AI workloads. However, manual migration from SAS to Fabric is complex, time-consuming, and risky due to differences in programming models, data processing engines, and execution environments.

SAS to Microsoft Fabric Automated Migration is an AI-powered SaaS solution that accelerates SAS modernization by converting SAS programs, ETL jobs, and analytics workflows into Microsoft Fabric–native assets, including Fabric Notebooks (PySpark), SQL for Fabric Warehouse, Dataflows Gen2, Pipelines, and Lakehouse tables.

The platform automates discovery, translation, deployment, and validation of SAS workloads on Fabric, enabling organizations to modernize faster with lower risk and higher confidence. It supports large-scale portfolio migration, ensures data quality parity, and optimizes workloads using Fabric-native performance patterns.

This solution is designed for enterprises looking to retire or reduce dependency on SAS, consolidate analytics platforms on Microsoft Fabric, and accelerate cloud data and AI adoption.

Business outcomes:

• Accelerated SAS to Fabric migration

• Reduced migration cost and risk

• Improved performance using Fabric-native execution

• Automated validation and data quality assurance

• Enterprise-ready governance and CI/CD integration

Automated SAS Portfolio Discovery

• Scans SAS programs, jobs, and libraries

• Extracts dependencies, data sources, macros, and schedules

• Generates migration readiness and complexity score

AI-Powered SAS Code Conversion

• Converts SAS Base, SQL, and ETL logic to PySpark & Fabric SQL

• Translates data preparation and transformation logic

• Supports batch pipelines and scheduled workloads

Fabric Asset Auto-Creation

• Auto-generates Fabric Notebooks, Pipelines, and Dataflows Gen2

• Creates Lakehouse and Warehouse schemas

• Supports CI/CD deployment across environments

Use Cases

• SAS to Microsoft Fabric migration

• SAS modernization and cloud migration

• Legacy analytics platform modernization

• Data engineering platform consolidation

• Cost optimization by reducing SAS footprint

• AI and advanced analytics enablement on Fabric