How is data validation performed during the transformation stage in DTS?

During the transformation stage in DTS (Data Transformation Services), data validation is performed by applying validation checks and rules. This process is crucial to ensuring that the data being transformed meets certain quality standards and is suitable for the intended use.

Applying validation checks and rules allows for systematic verification of data types, formats, ranges, and relationships within the data. It helps identify and rectify errors, such as data inconsistencies or format mismatches, before the data is loaded into the target system. By leveraging predefined rules during transformation, organizations can maintain data integrity and enhance the reliability of their data-driven processes.

The other methods mentioned are less effective for this particular context. Manual entry of data does not typically apply to the transformation stage, as that phase is more about processing and transforming existing data rather than entering new information. Third-party tools can assist with various aspects of data management but are not specifically tied to the built-in validation mechanisms within DTS. Code compilation relates more to programming languages and software development rather than data transformation workflows.