Data Transformation Tables
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Foundations data transformation tables enable you to transform data received in a message so that it is appropriate for the target field in the subscribing application. You can create data transformation tables that contain one or more data transformations. Each data transformation contains one or two source values and the target value.
When you create a mapping on a messaging relationship, you can optionally specify a data transformation table to apply. For example, you might receive messages via a subscription that contain information about people and their job roles. If a message contains information regarding an architect with one year's experience, you can create a data transformation table to convert this into a specific job role of Junior Architect.
Source Value 1 | Source Value 2 | Target Value |
---|---|---|
Architect | 1 year | Junior Architect |
In this second example, a senior business analyst is transformed to a business analyst. The optional source value 2 is not used.
Source Value 1 | Source Value 2 | Target Value |
---|---|---|
Senior Business Analyst | Business Analyst |
The following table provides examples of mappings that include two sources for data transformation.
Source Value 1 | Source Value 2 |
Matching Value for Source Value 2 on Data Transformation |
Data Transformed |
Actual Target Value |
---|---|---|---|---|
Developer | 1 year | Yes | Yes | Junior Software Developer |
Developer | Yes (null) | Yes | Software Developer | |
Senior Business Analyst | Yes (null) | Yes | Business Analyst | |
Senior Business Analyst | No | No | Senior Business Analyst |