Predefined transformations
The Predefined Transformations feature in AnalyticsCreator defines reusable data transformation rules that can be automatically applied to columns based on metadata conditions. These transformations are evaluated during project generation and allow standard logic to be applied across tables.
Function
Predefined transformations evaluate column metadata (e.g., data type, length, nullability) and apply standardized SQL expressions where matching rules are met. They are primarily used to enforce data quality, formatting, or anonymization logic without manual scripting at the column level.
Access
Predefined transformations are managed under the DWH > Predefined trans. module. Each transformation includes a name, rule conditions, and the resulting SQL expression. A set of predefined rules is available by default and can be extended with custom logic.
Properties
| ID | Property | Description |
|---|---|---|
| 1 | Name | Unique identifier for the transformation rule |
| 2 | Description | Optional field for describing the transformation’s purpose |
| 3 | Check Statement | Condition that defines when the transformation should apply, based on column metadata |
| 4 | Transformation Statement | SQL expression applied to the column if the check condition is met |
| 5 | Evaluated Statement | Dynamic result preview of the transformation based on metadata values |
| 6 | Allowed Keywords | Metadata fields available for use in the check and transformation statements |
| 7 | Evaluate | Runs a preview of the evaluated logic using current metadata context |
| 8 | Cancel | Discard changes to the transformation and close the editor |
| 9 | Save | Commits the transformation changes to the project metadata |
Screen Overview
Predefined Transformations List
The image below shows the List Predefined Transformations interface with columns labeled for easy identification.
Predefined Transformations Edit
This screen appears when selecting an existing transformation or clicking New. It allows editing rule logic and behavior.
Behavior
- Transformations are evaluated per column based on the Check Statement
- Matching columns receive the Transformation Statement during code generation
- Multiple predefined transformations may apply to different column types or rules
- Transformations are reusable and can be centrally maintained
- They can be referenced inside Macros to simplify expression reuse across objects
- The Evaluate button allows previewing of logic before committing changes
Allowed Keywords
The following metadata keywords are available for conditional logic and expression generation:
Column_NameCharacter_Maximum_LengthNumeric_ScaleNumeric_PrecisionIs_NullablePK_Ordinal_PositionSrcTypehasLengthhasPrecisionhasScaleSrcSSISTypeAnonymization_check_statementAnonymize
Notes
- Predefined transformations are static and applied at generation time
- All transformation logic must be valid T-SQL
- They support logic centralization and reuse across multiple parts of the model
- They do not modify source data but influence how columns are handled in the generated SQL layer
