A dynamic entity points to data residing in an external data source. Unlike real entities, where data is fully loaded/imported into the Trillium repository, dynamic entities allow you to work directly with the external data although the data is never overwritten unless manually refreshed.
Dynamic entities:
- Are created faster than real entities.
- Allow you to refresh or point to a different data source when used as part of a Quality process.
Dynamic entities are very useful in the planning phase of a Quality cleansing project, especially when there are thousands or millions of records. You can create dynamic entities with only a few hundred records, apply business rules and configure a Quality cleansing project. This can act as a template to help analyze the results from the sample data and validate that the rules, requirements and standards in the project meet your requirements.
Dynamic entities are also useful in projects that need to run at a regular interval. For example, you can create dynamic entities as a template to store business rules in multiple entities grouped in a Baseline Analysis project and then run the rules each time the source data is updated. The data may be updated every week, month or quarter. Once updated, you can simply copy the project, load the data into the new project and get the business rule results automatically without having to reapply them.
Because a dynamic entity is not loaded with data, it cannot evaluate attribute business rule compliance for an entity. Moreover, in a dynamic entity, the data is not fully indexed or analyzed. Therefore, it takes longer to filter, run business rules and drill down on data as compared to a real entity.
Also, dynamic entity cannot be used for:
- Discovery keys or dependencies
- Create keys or dependencies
- Re-analyze business rules
- Analyze pending derived metadata