What function does data transformation perform in DTS?

Data transformation is a crucial process in the data integration lifecycle, particularly within Data Transformation Services (DTS). Its primary function is to clean and convert data, ensuring that it is in the correct format for analysis, reporting, or loading into a target system. During this transformation process, various operations can be applied to the data, such as changing data types, filtering records, aggregating values, and applying business rules to enhance data quality.

By focusing on transforming data, individuals or organizations enhance the usability and reliability of their data, making it more suitable for analytical processing or integration into databases. This step is essential before data can be effectively loaded into a destination database or data warehouse, as it ensures that the data adheres to the necessary standards and formats.

The other options pertain to different aspects of data management: loading data into databases primarily deals with the movement of data, backing up data relates to creating copies for recovery purposes, and storing data securely pertains to ensuring the safety and integrity of data. While these are also important functions in data processing, they do not address the specific role that data transformation plays in refining and preparing data for subsequent use.