Market Context
Between 30% and 40% of mainframe JCL batch cycles consist of heavy data transformations using SyncSort or DFSORT parameter cards. Modernizing these batch windows into Snowflake or Databricks ETL pipelines is a multi-billion dollar industry.
The Gap
GitGalaxy successfully parses the JCL step calling SORT, but it treats the embedded SYSIN control cards as opaque text. We lose visibility into the exact fields, byte offsets, and transformation logic of the data.
Required Action
Build a parameter-card parser for DFSORT/SyncSort that explicitly maps SORT FIELDS=..., INCLUDE COND=..., and OUTREC transformation statements. Extracting these parameters will eliminate a massive "dark matter" gap in enterprise ETL batch lineage mapping.
Market Context
Between 30% and 40% of mainframe JCL batch cycles consist of heavy data transformations using SyncSort or DFSORT parameter cards. Modernizing these batch windows into Snowflake or Databricks ETL pipelines is a multi-billion dollar industry.
The Gap
GitGalaxy successfully parses the JCL step calling
SORT, but it treats the embeddedSYSINcontrol cards as opaque text. We lose visibility into the exact fields, byte offsets, and transformation logic of the data.Required Action
Build a parameter-card parser for DFSORT/SyncSort that explicitly maps
SORT FIELDS=...,INCLUDE COND=..., andOUTRECtransformation statements. Extracting these parameters will eliminate a massive "dark matter" gap in enterprise ETL batch lineage mapping.