Customer Demo

Automate Your SAS Modernization

Base SAS · Enterprise Guide (EGP) · DI Studio · SAS Viya
Migrate to Python, Snowflake, Databricks & more at 10X speed

Python PySpark Snowpark Snowflake Databricks BigQuery

On-premise · Air-gapped · Self-service · No consultants needed

2

The Challenge

Legacy SAS Environments Are Holding You Back

Organizations face massive legacy estates with no clear path forward.

Massive Scale

Hundreds of thousands of files with no visibility into what's actively used versus stale data.

Mounting Costs

Growing SAS license fees and storage costs — much of it for unused, dormant programs and datasets.

Unknown Dependencies

Complex web of programs, macros, and datasets. What connects to what is unknown without automation.

Migration Risk

Can't migrate everything at once. Need data-driven prioritization, not guesswork.

Time Pressure

Manual analysis takes months. The business needs a clear, prioritized plan — fast.

Vendor Lock-in

Proprietary formats, proprietary language, proprietary tooling. Every year the exit cost grows.

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SAS2PY by SAS2PY

Automated, Parser-Driven SAS Modernization

Parser-driven engine — deterministic, explainable, auditable conversions. Not AI-only guesswork.
10X speed — convert thousands of SAS programs in days, not months.
Multi-target output — Python, PySpark, Snowpark, SQL for Snowflake, Databricks, BigQuery, Fabric, and more.
Fully on-premise — no data leaves your environment. Air-gapped operation supported.
Self-service — deploy in under an hour. No consultants, no RFP, no waiting.
End-to-end — from discovery and lineage through conversion, execution, and validation.

10X

Faster Migration

vs. manual rewrite

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Inputs

What We Ingest

Everything from your SAS ecosystem — programs, platforms, and data sources.

SAS Programs & Code

Base SAS programs (.sas)
DATA steps & SET / MERGE
PROC SQL & pass-through
PROC steps (SORT, MEANS, FREQ, TRANSPOSE)
Macros & %INCLUDE chains
Formats, Informats & PROC FORMAT
ODS & SAS/STAT

SAS Platforms

SAS DI Studio (ETL jobs)
Enterprise Guide (EGP)
SAS Viya & CAS engine
Management Console
Stored Processes
Grid Manager & scheduling

SAS Data Sources

SAS datasets (.sas7bdat)
Oracle, SQL Server, Teradata
DB2, Netezza via SAS/ACCESS
Flat files, CSV, Excel & XML
ODBC & bulk-load connections

Also Supported

IBM DataStage Oracle ODI Teradata BTEQ Informatica Alteryx Mainframe JCL PL1 VBA

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Outputs

Targets We Generate

Python Ecosystem

PySparkDistributed DataFrame and SQL workloads

SnowparkPython APIs for Snowflake compute

DatabricksDelta Lake pipelines and notebooks

DataprocManaged Spark on Google Cloud

FabricMicrosoft Fabric Lakehouse and pipelines

EMRAWS EMR Spark and Hive workloads

ClouderaOn-prem or hybrid Hadoop distributions

Modern Warehouse & Deployment

SnowflakeCloud data warehouse

BigQueryGoogle Cloud analytics

RedshiftAWS data warehouse

IcebergOpen table format

Deployment Targets

dbt Airflow Openflow Git / CI

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🧭

Compass

Migration Intelligence

Understand Your Estate Before You Migrate

Scan, score, and classify every asset as MIGRATE, ARCHIVE, or DELETE.

Complete Inventory — automated scanning of every file, program, and execution log.
Smart Classification — multi-factor scoring: usage, recency, size, complexity, execution quality.
Dependency Mapping — parse code to extract relationships and external references.
Cost Optimization — identify archival and cleanup opportunities. Project savings before committing.

Classification Output

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MIGRATE — Critical
High value, low effort. Phase 1.

3-4

MIGRATE — Standard
Active workloads. Phase 2-3.

A

ARCHIVE
Move to cold storage. Reduce licensing costs.

D

DELETE
Duplicates, orphans, test data. Safe to remove.

60–80%

Data Reduction

Archive or cleanup candidates

5–10X

Analysis Speed

vs. manual assessment

Hours

To Complete Scan

Not weeks or months

100%

Asset Coverage

Complete inventory visibility

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Methodology

Migration Process

Three phases plus go-live — systematic, repeatable, proven at enterprise scale.

1. Analyze & Insights

Automatic code assessment for rationalization and migration planning
Comprehensive dependency mapping with data and file lineage
Development of required frameworks and standards
Code complexity analysis, block labels, and LoC assessment
Rationalize and standardize current ETL

2. Convert & Migrate

Automated SQL and ETL code translation with modernization
Multi-target conversion with optimization and unit testing
Metadata preservation and comprehensive documentation
Visual execution on Databricks, Snowflake, and cloud platforms
Native integration with dbt, Airflow & Git

3. Test & Validate

End-to-end automated testing of data pipelines
Comprehensive data validation and schema mapping
Side-by-side output comparison and metrics validation
Test data generation and cutover preparation
Partitioned validation with automated error detection

Go Live & Hyper Care

Streamlined transition with dedicated support and monitoring to ensure optimal performance

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Platform Walkthrough

Five Steps. One Platform.

Each step is a live module you can demo interactively.

1

Analyze — Inventory & Lineage

Scan SAS to auto-build a complete inventory. Discover dependencies, macro chains, external calls, and data sources. Produce visual lineage and impact maps.

InventoryLineageComplexityValidationRisk

2

Convert — Generate Modern Code

Parser conversion into Python, PySpark, Snowpark, and SQL. All translations are explainable and auditable. Auto-documentation for each artifact.

PythonPySparkSnowparkSQLAuto docs

3

Execute — Orchestrate Pipelines

Run converted workloads in the right order. Visual execution on Databricks and Snowflake. Native dbt, Airflow, and Git integration with centralized logs.

Visual orchestrationSchedulingRetriesCI ready

4

Validate — Prove Parity

Partitioned validation compares row-level and aggregate outputs between legacy and modern systems. Automatic schema checks and data matching reports.

Row countsCommon columnsMismatchesEvidence

5

Merlin AI — Assist & Accelerate

Context-aware assistant that knows your inventory, lineage, and conversion plans. Generate unit tests, explain diffs, suggest mappings. Enterprise-safe — runs in your environment.

Inline explainsMapping assistTest scaffoldSecure

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Modules

Modernize Faster Across the Full Lifecycle

Code Analysis

Assess thousands of scripts, map complexity and dependencies, flag readiness. Clear scope and a prioritized plan.

Visual Lineage

Visualize code across jobs, tables, and SQL. See sources, flows, and changes. Impact checks and audit support.

Code Conversion

Convert SAS, DataStage, BTEQ and more into Python, PySpark, Snowpark, or SQL with matched outputs.

Data Mapper

Automatically map legacy schemas to Snowflake or Databricks. Enforce naming and data types with audit-ready visibility.

Auto Docs

Automatic documentation captures legacy and target code, detailing components, parameters, and dependencies.

Data Matching

Compare source and target outputs at scale using configurable keys. Flag mismatches, duplicates, and gaps.

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Execution

Visual Execution

Run directly on Snowflake and Databricks with step-by-step visibility.

Live warehouse session — visual lineage combined with live code in one workspace. See each step and the exact failure point.
Streamlined troubleshooting — cuts retesting, provides audit-ready logs, lowers engineering and compute costs.
Lower risk — visual lineage shows upstream and downstream impact, so teams retest only what matters.
Native integration — connects to dbt, Airflow, and Git for CI/CD pipelines.

▶

Live Demo

Visual Execution on Snowflake & Databricks

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Deployment & Security

Private by Design. You Hold the Keys.

Deployment Options

Docker container or Windows VM — one-command install, running in under an hour
Cloud-ready: AWS EC2, Azure D8s, Google Cloud n2-standard-8
Internal services: VS Code Server, nginx proxy, Backend API, PostgreSQL, Jupyter, Merlin
Volume mounts for workspace, SSL, and Postgres data persistence

Security Posture

Fully air-gapped operation supported — zero outbound connections
SSL for VS Code, Jupyter, nginx proxy, and backend API
No source code or data ever leaves your network
Secrets managed in your KMS (AWS KMS, Azure Key Vault, Google Cloud KMS)
Audit logs remain in CloudWatch, Log Analytics, or Cloud Logging
Role-based access, SSO/MFA integration, fine-grained permissions

AWS

VPC · PrivateLink · S3 · ECR · KMS · CloudWatch

Azure

VNet · Private Endpoints · ADLS · ACR · Key Vault

Google Cloud

VPC · Private Service Connect · GCS · Cloud KMS

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Self-Service Pilot Options

Run the Pilot Yourself

No consultant. No RFP. Install SAS2PY, convert real code, and see results — on your own terms.

Migration Readiness

1 week

Discovery & Insights

Scope: 100K LoC — Unlimited
Inventory workflows, macros, and configs
Dependency mapping with visual lineage
Complexity analysis with block labels and LoC
Reports: Inventory, lineage, and risk assessment

Full Pilot

4–6 weeks

End-to-end

Discovery + 10K LoC conversion
Pilot code conversion to target system
Data matching and validation
Enterprise data workflows
Full project reports with executed code

Large Scale Pilot

2–4 months

Enterprise

1M LoC discovery
100K LoC conversion
Full end-to-end validation
Enterprise execution and reporting
Full project and JCL reports

Capability	Migration Readiness	Full Pilot	Large Scale Pilot
Discovery	100,000 LoC	100,000 LoC	1 Million LoC
Conversion	N/A	10,000 LoC	100,000 LoC
Duration	1 week	4–6 weeks	2–4 months
Reports	Inventory, lineage, risk	Full project	Full project + JCL
Execution	In your environment	In your environment	In your environment

All pilots are fully self-service — install, run, and evaluate independently. No external consultants required.

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Get Started

Ready to Modernize?

Schedule a demo or start a self-service pilot today. See SAS2PY parse your own SAS code in a live walkthrough.

Schedule Demo → Request a POC →

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