SAS Migration Suite

Why T1A

Data Modernization Experts with SAS DNA

Most migration partners approach SAS migration as a code conversion task. We built our practice from deep SAS expertise — because understanding your existing environment is what determines whether the migration succeeds.

Former SAS Platinum Partner — 5 years Platinum, 10 years Gold

Deep SAS Expertise

As a former SAS partner, we know first-hand the capabilities, patterns, hidden complexities and intricacies of SAS software.

Acceleration Tooling

Our purpose-built suite automates code analysis, conversion, validation, and change management — cutting timelines and costs significantly versus manual approaches.

Phased, Risk-Mitigated Delivery

We carefully plan migrations with a phased approach, where each phase includes complete workload migration, user training, and SAS decommissioning for targeted teams.

Flexible Engagement Models

From fully managed "White-Gloves" migration to self-service migration and support — we tailor the engagement to your organization's capabilities and preferences.

The Opportunity

Why Migrate to Databricks?

Moving from legacy SAS to a modern data platform unlocks significant advantages across cost, performance, and talent.

Lower Cost

Significantly lower than on-prem costs with cloud-native pricing and pay-as-you-go compute.

Scalable

Easily grows or shrinks to fit your needs — from small team workloads to enterprise-scale processing.

Dynamic

Constant updates with new features, AI/ML capabilities, and community-driven innovation.

Mainstream

Built on popular open-source tech with wide talent availability — Python, Spark, and SQL.

Faster

Uses the latest distributed computing tech for better performance on large-scale data operations.

Future Proof

Aligns with future IT strategies, cloud-first initiatives, and organizational growth.

The Challenge

Migration Pain Points

SAS migration is more than code translation. These challenges determine whether projects succeed within budget and timeline.

Complex Ecosystem

Legacy platforms involve multiple components with various complex functions, often uncovered only during migration.

Beyond Code Translation

Migration of business processes, data and user adoption often pose a greater challenge than code.

Scope & Strategy

Migration projects need a well-defined scope and strategy to succeed within budget and timeline.

User Adoption

Enablement and empowerment of users in the target platform is crucial for long-term success.

Our Approach

The Full SAS Migration Journey

A structured, iterative path from SAS landscape discovery through full organizational go-live on your modern data platform.

Discover & Plan

Technical interviews with IT stakeholders & SAS Admins
Platform analysis: SAS logs, artifacts, metadata & more
Business interviews & dependency mapping
Usage inventory, workload & migration roadmap

1–3 months

Proof of Concept

Initial platform & migration flow setup
Showcase migration of select SAS processes
Stakeholder & end-user demos
Early adoption: complete migration of proactive teams

2–4 weeks

Data Enablement

Enable required sources and destinations in the target platform
Connect to external data sources
DWH migration to the cloud Lakehouse
Platform development & hardening

Per phase

Artifacts Conversion & UAT

Convert SAS artifacts to the target platform
Automated conversion with Alchemist
Fixes, refactoring & end-to-end validation
UAT: validate code & result datasets

Per phase

People Enablement & Go-Live

Customized trainings for all roles
Flexible support for business and IT
Coexistence between SAS and target platform
SAS decommissioning & managed hypercare

Per phase

Alchemist SAS Migration Suite

Purpose-Built Tools That Accelerate Every Phase

Our tooling suite automates the most time-intensive aspects of SAS migration — from initial discovery through code conversion and change management. Each component works as part of an integrated suite.

Assessment

Code Analyzer

Static analysis of SAS code artifacts — programs, macros, EG flows, and DI jobs. Produces a full inventory with complexity metrics.

Complexity analysis by workload type
Usage pattern breakdown
Dependency mapping
Duplicate identification

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Logs Analyzer

Automated workload discovery from SAS execution logs. Identifies active jobs, real usage patterns, data access events, and lineage.

Session & submission activity
Data access event tracking
Library & data source mapping
User & team attribution

Metadata Analyzer

Extracts and inventories the full SAS metadata environment — libraries, servers, deployed jobs, stored processes, and info maps.

SAS library & dataset catalog
Deployed jobs & stored processes
Information maps & BI objects
Auth domains & connections

Migration

Code Converter

Automated SAS-to-PySpark conversion engine. Translates programs, macros, and EG flows into native PySpark with side-by-side review.

SAS to PySpark automated conversion
99% coverage of SAS instructions
Conversion logs & quality reporting
Batch processing for large codebases

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Agentic Flows

End-to-end agentic migration pipeline. Deploys jobs, runs unit and E2E tests, and iterates with LLM agents until all tests pass — automatically.

Automated job creation & deployment
LLM agent-assisted bug fixing loop
Unit & E2E test execution
Validation reports & artifacts

Change Management

Centrally manage all aspects of the migration across teams, business streams, and phases. Gantt timeline, work items, and incident management.

SAS inventory tracking
Work items & UAT records
Migration progress dashboards
Incident management

User Empowerment

Bringing SAS Users Confidently into Databricks

Migration is more than code conversion — it's people. We invest in trainings, self-serve tooling, and a coexistence framework so analysts and data scientists keep delivering from day one.

Hands-on Trainings

Role-tailored, interactive learning paths that take SAS users from familiar patterns to confident Databricks delivery.

Customized programs for analysts, data scientists & engineers
SAS → PySpark translation patterns and idioms
Notebooks, jobs & Lakehouse fundamentals
Office hours and post go-live support

Alchemist as a Self-Serve Tool

Users translate, validate and run their own SAS code without filing tickets — directly inside Databricks.

Alchemist UI for interactive SAS-to-PySpark conversion
Alchemist for Genie — natural-language SAS migration
Copilot & Cortex integrationsComing Soon
Secure and in-platform — code never leaves the workspace

SAS–Cloud Coexistence Framework

A staged bridge that lets SAS and Databricks operate side by side, removing big-bang risk and giving each team time to adopt at their pace.

Shared data access between SAS and Databricks
Phased workload cutover — no big-bang switch
Familiar workflows preserved during transition
SAS decommissioning at each team's own pace

Case Studies

Select SAS Migration Cases

Real results for leading organizations across industries — financial services, healthcare, energy, media, and more.

8 months

Electric Utility Company, USA

Migrated SAS code to a modern data platform using Alchemist, implementing Lakehouse architecture and an end-to-end ETL framework for the entire data engineering org.

4 months

Health Insurance Company, USA

SAS EG analytics projects migration to a modern data platform, with full consulting, user training, and a seamless transition for business analysts and data scientists.

5 months

Healthcare Company, Japan

SAS EG data flows migration to a modern data platform — established full Lakehouse architecture and user transition with 180+ production pipelines migrated.

Public References