https://catalogartifact.azureedge.net/publicartifacts/hexawaretechnologiesltd-nj1734355056208.modernize-sas-to-pyspark-assessment-851e94b8-eb4c-4822-8c97-25336b07f3f5/5f894b5e-8aa6-4dc0-a499-85eeb9bd3b61_HexawareLogo280.png

Modernize SAS to Cloud Native Solutions

Hexaware Technologies Inc

Eliminate license cost and enhance scalability by modernizing your SAS workloads to PySpark—Comprehensive assessment, Pilot for 50 SAS scripts, and a clear roadmap to transform your entire environment

Hexaware’s SAS to PySpark modernization offering enables enterprises to transform legacy SAS analytics workloads into scalable, cloud-native PySpark pipelines. By migrating to PySpark, clients benefit from up to 40-60% TCO reductions by eliminating expensive SAS licensing and leveraging cost-effective cloud infrastructure. This modernization accelerates data processing by 3-5x, improves scalability to handle growing data volumes, and integrates seamlessly with advanced AI and analytics ecosystems.

Hexaware’s US patented AI-powered Amaze® accelerator accelerates automation up to 70% of the SAS-to-PySpark conversion including complex macros and conditional logic, reducing manual effort and errors. The platform also performs AI-based validation using hash-based row-level data comparison to ensure output parity and detect anomalies early. Integrated with DevOps workflows and CI/CD pipelines, Amaze® accelerates deployment and enables continuous quality assurance.

The offering starts with an automated assessment that analyzes SAS scripts, macros, and dependencies to deliver detailed complexity and fit-gap insights. This enables precise prioritization and a low-risk migration strategy. A pilot migration of 50 SAS scripts validates automated conversion accuracy, functional parity, and performance improvements, showcasing the strength of our AI-enabled code conversion.

Key Features:

  • Automated SAS workload inventory, dependency analysis, and complexity scoring
  • AI-powered automated conversion of SAS programs, macros, and workflows to PySpark code
  • Pilot migration of 50 scripts validating conversion accuracy, data integrity, and performance
  • AI-driven data validation ensuring functional and numerical equivalence with existing SAS workflows
  • Cloud-native PySpark architecture deployment supporting scalability, elasticity, and AI workloads
  • Integration with DevOps pipelines for automated testing, deployment, and monitoring
  • Robust security, compliance, and governance throughout the modernization lifecycle

Business Benefits:

  • Reduce analytics TCO by 40-60% by eliminating SAS licensing and scaling cost-effectively with PySpark
  • Achieve 3-5x faster processing on large datasets via distributed Spark architecture
  • Accelerate modernization timelines by ~50% using Amaze® automation
  • Increase agility with cloud-scale, parallel data processing pipelines
  • Future-proof analytics with seamless AI/ML readiness and native cloud integration

Outcomes:

Clients gain confidence and value from a validated pilot migration of 50 SAS scripts, forming the foundation of an enterprise-wide PySpark modernization roadmap. Hexaware’s AI-powered, automation-led approach minimizes risk and manual effort, enabling faster, cost-effective adoption of cloud-native analytics platforms. This transformation delivers measurable cost savings, enhanced agility, and a future-proof foundation for data-driven innovation.

Key Azure Services:

Azure Databricks, Azure Synapse Analytics, Azure Data Factory, Azure Blob Storage, Azure Devops, Azure Key Vault, Azure Monitor, Azure Active Directory

At a glance

https://catalogartifact.azureedge.net/publicartifacts/hexawaretechnologiesltd-nj1734355056208.modernize-sas-to-pyspark-assessment-851e94b8-eb4c-4822-8c97-25336b07f3f5/0ec97f87-385f-4eff-9322-54bf0896280c_SAStoPyspark.png