Split Transformation
Split a single table into multiple tables by assigning specific columns to each.
Split a single table into multiple tables by assigning specific columns to each.
Bring specific data-processing tools into a transformation to support your workflow.
Link a data rule to a transformation to enforce data-quality and governance requirements.
Replace a data source in a workflow by selecting new tables and schemas.
Create a copy of an existing transformation table to reuse or modify its configuration.
Add intelligent System Agent AI processing to your data transformations.
Enhance data processing by adding specialized Custom Agentic AI agents to a transformation.
Split a structured text field into multiple columns for richer analysis.
Process data using Spark's Python API with a PySpark transformation.
Apply SQL queries to modify and analyze data directly within a workflow.
Create a structured storage endpoint where processed data is written.
Remove an unwanted transformation from your workflow.