Column-level lineage and Source-to-Target Mapping across every language, SQL dialect, and ETL tool in your enterprise — from SAS and Python to Informatica and Snowflake. One unified atlas of every data flow.
Atlas ingests code from every platform in your stack — programming languages, SQL dialects, ETL tools, BI layers — and produces a unified, column-level map of how data flows across your entire organization.
Powered by MigryX Compass parsers + SQLForge engine + Merlin AI
Enterprises run SAS alongside Python notebooks, PySpark pipelines feeding Snowflake, Informatica workflows loading BigQuery, and Alteryx automations transforming Polars DataFrames. Atlas is the first platform that generates a unified, column-level atlas of data lineage across all of them — in one place.
SAS, Python, PySpark, R, Polars, Scala — plus every SQL dialect and ETL product MigryX supports. One lineage graph for your entire data estate.
Not approximate — deterministic. Custom-built parsers trace every column from raw source to final output with transformation logic preserved.
Automatic Source-to-Target Mapping with transformation details, operation types, and module references — exportable to CSV, JSON, and Excel.
Merlin AI analyzes your lineage graph to surface risks, detect anomalies, prioritize migrations, and answer questions in natural language.
Use Atlas as the foundation to build certified, governed data products with built-in lineage, quality metrics, and full traceability.
Understand your entire legacy landscape before migrating. Atlas shows exactly what exists, what depends on what, and the safest path to modernize.
Atlas accepts code and metadata from programming languages, SQL dialects, ETL products, BI tools, and cloud platforms — and unifies them into a single lineage graph.
Plus mainframe languages (JCL, COBOL, PL/1, RPG/AS400) and stored procedure objects (DDL, Views, UDFs, Triggers)
Your SAS lineage tool can't see Informatica. Your SQL tracer can't read Python. You get fragments, never the full picture.
Teams spend weeks manually building Source-to-Target Mapping spreadsheets that are outdated the moment they're finished.
Without cross-platform lineage, modernization projects miss hidden dependencies and break production pipelines.
Regulators want end-to-end traceability. You can't prove it if your lineage stops at the boundary of each tool.
Atlas traces data flows across programming languages, SQL dialects, and ETL products in a single view. File-level, project-level, and column-level lineage — unified.
Trace data from a SAS program through a Python transformation into a Snowflake table — column by column, across language boundaries.
Informatica mappings feeding Databricks notebooks running PySpark that loads BigQuery — Atlas maps every hop.
Every column traced from source to target with transformation logic, operation type, and module reference — deterministic, not approximate.
Click any column to see everything that feeds it and everything it feeds — across the entire enterprise, not just one tool.
Atlas Lineage Graph
Parse SAS, Python, PySpark, R, and Polars to extract dataset reads, writes, joins, aggregations, and column transformations — all mapped to the unified graph.
Column-level lineage from 15+ SQL dialects — stored procedures, views, CTEs, window functions, and vendor-specific extensions parsed natively.
Informatica mappings, Talend jobs, Alteryx workflows, DataStage sequences, SSIS packages, ODI interfaces — all parsed into the same lineage model.
Export lineage and STTM to CSV, JSON, Excel, and interactive HTML reports. Feed data catalogs, governance tools, and compliance workflows.
Atlas generates comprehensive Source-to-Target Mapping automatically — no manual spreadsheets, no consultants. Every column, every transformation, every dependency captured with precision.
Trace exactly how each target column is built from source columns — with join conditions, aggregation logic, CASE expressions, and window functions documented.
Each mapping step is classified: direct copy, type cast, aggregation, join, filter, lookup, pivot, concatenation, calculation — machine-readable and auditable.
Follow data through multiple transformation steps: raw table → staging view → PySpark join → Snowflake mart → Power BI dashboard. Every hop captured.
STTM exports to Excel (multi-sheet), CSV, JSON. Integrate with Collibra, Alation, Atlan, or any data catalog via API or file import.
STTM documentation satisfies SOX, GDPR, CCPA, and BCBS 239 requirements for data lineage traceability. Audit-ready out of the box.
Merlin AI augments parser-generated STTM: filling gaps in dynamic SQL, resolving ambiguous column references, and scoring mapping confidence.
Five stages transform raw source code from any language, dialect, or tool into a unified, queryable lineage graph.
What Atlas Delivers
Moving from SAS to Databricks? Informatica to Snowflake? Atlas maps every dependency before you migrate — so you know exactly what's at stake and the safest sequence to modernize.
Use Atlas lineage as the foundation for certified, governed data products. Every product comes with built-in traceability, quality metrics, and SLAs from day one.
Prove end-to-end data lineage for GDPR, CCPA, SOX, BCBS 239 — across SAS, SQL, Python, and ETL tools. Generate audit-ready reports in minutes.
Before changing a source table, see every downstream pipeline, report, and dashboard affected — across all languages and tools, not just one platform.
Feed Collibra, Alation, Atlan, or Unity Catalog with rich, parser-generated lineage metadata that goes far beyond what those tools can extract on their own.
Identify redundant transformations, bottleneck datasets, and unused pipelines across your entire estate. Reduce cloud costs 40–60% through lineage-driven optimization.
Most lineage tools only understand SQL or only one ETL platform. Atlas covers everything.
| Capability | MigryX Atlas | Typical Tools |
|---|---|---|
| Programming language lineage (SAS, Python, PySpark, R, Polars) | ✓ | ✗ |
| 15+ SQL dialect support with vendor extensions | ✓ | ~ |
| ETL product lineage (Informatica, Talend, Alteryx, DataStage, SSIS) | ✓ | ✗ |
| Cross-platform column-level lineage | ✓ | ✗ |
| Automated STTM generation | ✓ | ✗ |
| Custom parser architecture (deterministic, zero guesswork) | ✓ | ~ |
| Parser-driven analysis with optional AI & natural language querying | ✓ | ✗ |
| On-premise / air-gapped deployment | ✓ | ~ |
| Migration impact analysis across all platforms | ✓ | ✗ |
| Data catalog integration (Collibra, Alation, Atlan) | ✓ | ~ |
✓ Full support ~ Partial / approximate ✗ Not supported
Full deployment behind your firewall with zero data leakage. No cloud egress required. Complete data sovereignty.
Enterprise identity management and role-based access control for teams of any size.
Run lineage analysis in your CI/CD pipelines. Catch breaking schema changes before they ship to production.
Process millions of code artifacts with distributed parsing. Built for the largest enterprise data estates.
OpenAI, Gemini, AWS Bedrock, Cortex, or custom GenAI backends. Your cloud, your model, your choice.
Dedicated success team with SLAs. White-glove onboarding for complex multi-platform environments.
Send us a sample of your code from any combination of SAS, Python, SQL, or ETL tools. We'll generate a cross-platform lineage atlas with full STTM — so you can see exactly what Atlas delivers.