General steps perform broad, essential transformations that apply to a wide range of use cases. These include copying or renaming fields, filtering records, applying business rules or formulas, generating unique keys, or executing custom code for advanced scenarios.
| Transform | Description |
|---|---|
| Copy Field | Copies a column to one or more new columns. |
| Filter Field | Removes selected columns from a table. |
| Filter Row | The row filter evaluates whether to include rows depending on a logical expression that evaluates to either true or false. |
| Evaluate Rule | The Evaluate Rule step allows users to create a step in Data Quality that evaluates a record based on an existing Data Catalog Rule. |
| Execute Formula | Performs operations on values and inserts the result in a new column. |
| Generate Key | Generates a unique key for each record, ensuring uniqueness across all datasets. |
| Custom Coding | The Custom Coding Step in the Data Quality Suite enables you to address advanced use cases or requirements that cannot be fulfilled using the existing Quality pipeline steps. |
| LLM Transform | This enables AI-driven modifications such as categorization, translation, and structured data extraction on pipeline data. |
| Make API Call | The Make API Call step lets you connect external APIs to your data pipelines by configuring sources, endpoints, and mapping parameters for smooth data exchange. |
| Rename Field | Renames a column in a pipeline. |
| Split Field | Splits a column into two new columns. |