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Complete the form below to get instant access to the SAS Modernization Checklist
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SAS estates hide business logic several macro calls deep, and span six interdependent layers that all have to move together. This checklist walks the three phases that get you there — map the estate, define your data products, then build and certify across all six layers.
Our SLMs extract logic buried in nested macros, catalog SAS7BDAT dependencies and hardcoded libnames, and map transformation logic down to the column. Full lineage means downstream reports don't break.
Historical utilization logs determine what gets rationalized. Redundant and dead jobs flagged for retirement, the rest scored against real usage, with schema and consumption patterns defined for each product.
Data access, transformation, models, reporting, scheduling, and governance — each layer rebuilt on its modern cloud-native equivalent, validated independently, then tested end to end.
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Enterprise modernizations completed
Faster time-to-market for AI-ready infrastructure
A multinational insurance and financial services provider accelerated legacy application modernization with Databricks and Delta Lake.
Read the case study to see how Next Pathway delivered:
A leading insurance and financial services provider modernized legacy data workloads with Databricks automation.
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ENDERLE GROUP
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THE BLOOR GROUP
Global Financial Firm Modernizes with Snowflake Migration.
Thinking beyond migration?
We help you modernize your data platform, end to end.
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