The following image shows a mapping that writes slowly changing dimension data to a Snowflake target table:

Add lookup and expression transformations to compare source data against the existing target data. You enter the lookup conditions and source columns that you want the Data Integration to compare against the existing target.

For each source row without a matching primary key in the target, the Expression transformation marks the new row. For each source row with a matching primary key in the target, the Expression compares user-defined source and target columns. If those columns do not match, the Expression marks the row changed. The mapping then splits into two data flows.

The first data flow uses the Router transformation to pass only new rows to the Expression transformation. The Expression transformation inserts new rows to the target. A Sequence Generator creates a primary key for each row. The Expression transformation increases the increment between keys by 1,000 and creates a version number of 0 for each new row.

In the second data flow, the Router transformation passes only changed rows to pass to the Expression transformation. The Expression transformation inserts changed rows to the target. The Expression transformation increments both the key and the version number by one.