What do "Transformation Rules" signify in the loading process?

"Transformation Rules" in the data loading process specifically refer to guidelines and protocols that dictate how incoming data should be cleaned, formatted, and manipulated to meet the requirements of the target system. This can involve various processes, such as transforming data types, standardized formats, or even applying business rules to ensure the data aligns accurately with the receiving application's needs.

By defining these transformation rules, implementers ensure the integrity and quality of the data being loaded, which is crucial for effective data utilization in decision-making and operational processes. Cleaning and formatting the data helps eliminate issues like duplicates, inconsistencies, or invalid entries, thereby enhancing the overall effectiveness of data integration efforts.

The other options pertain to different aspects of data loading. While the sequence of data processing focuses on the order in which data operations are performed, the documentation of data loads involves recording details about the loading process itself. The structure of data sources refers to the arrangement and organization of data before it is loaded, rather than the manipulation of that data. Thus, these aspects do not capture the essence of what transformation rules are intended to accomplish during the data loading process.