Convert SAS programs to AWS

How does SAS become AWS? SAS in. AWS out.

Deterministic parsers read the SAS estate and emit native AWS code, not SAS on an EC2 instance.

SAS programs → SAS2PY parser → Spark + S3 + Glue

SAS

Base SAS DATA step / macros

DI Studio Jobs + mappings

EG / EM Projects + flows

Viya / CAS CASL + actions

→

SAS2PY Parser

Deterministic parse AI where it helps

Row-level parity Before cutover

Spark emit EMR / Glue

DAG emit MWAA

→

AWS

Spark jobs EMR or Glue

S3 Iceberg / Delta

Glue catalog Replaces SAS libs

MWAA Replaces SAS Grid

CodePipeline CI/CD

Lambda Non-SQL remainder

MigryX AI handles the logic parsers cannot resolve alone, and every change it makes goes through the same parity checks. It runs on a model you approve, air-gapped if your estate requires it.

SAS library to an S3 table

A SAS libname plus a DATA step filter, emitted as Spark reading a Glue table on S3.

/* SAS */
libname dw 'sasdata';
data gold;
  set dw.txn;
  if amount > 1000;
run;

# libname → Glue / S3
gold = (
    spark.table("dw.txn")
         .filter("amount > 1000")
)
gold.write.format("delta").save("s3://lake/gold")

The SAS library is a catalog entry. The filter is a DataFrame predicate.

How is the conversion proven? Every conversion validated to row-level parity

SAS output compared to AWS output: row by row, column by column. Differences flagged before sign-off.