Which option correctly describes a Filter stage in data transformation?

The option that correctly describes a Filter stage in data transformation is the one that states it restricts results based on specified criteria. In a data transformation context, filtering is a critical function that allows users to refine their data sets by applying specific conditions. This process ensures that only the relevant data that meets certain requirements is included in the resulting output.

For instance, if you have a large dataset and you only want to analyze records from a specific date range or a particular category, you would use a filter to exclude all other data that does not meet those criteria. This capability is essential for focusing on the most pertinent information and improving analytical accuracy.

Filtering differs significantly from the other options. Combining multiple tables refers to the process of merging different datasets, while sorting involves arranging the data in a particular order. Aggregating values entails summarizing data points, such as calculating averages or totals. Therefore, while these are all important stages in data transformation, the defining characteristic of a Filter stage is its focus on restricting the dataset to only include data that fulfills certain conditions.