Which component is essential for data cleansing in DTS?

Data cleansing is a crucial step in data integration and preparation, and it involves identifying and correcting errors in data to improve its quality. The essential component for this process in Data Transformation Services (DTS) is the Data Transformation components.

These components specifically focus on transforming data during the extraction and loading processes. They allow users to apply various transformation operations, such as validation, cleansing, and standardization of data, to ensure that the information being processed meets quality standards. For example, these components can be utilized to filter out invalid entries, correct formatting errors, deduplicate records, or convert data types, thereby enhancing the overall integrity and usability of the data.

The other components mentioned, such as Workflow, Connection, and Control flow components, serve different purposes. Workflow components orchestrate the steps of data processing but do not actively engage in cleansing data. Connection components are responsible for establishing connections to data sources and destinations, while Control flow components manage the execution of tasks but do not perform transformations themselves. Thus, the Data Transformation components are vital for the actual cleansing tasks in DTS.