Which aspect is NOT part of data aggregation?

Data aggregation involves a variety of processes aimed at summarizing and transforming raw data to allow for easier analysis and interpretation. Summarizing data is crucial in aggregation as it helps in generating insights through metrics like averages, totals, or counts. Combining multiple data sources is also a key component, as aggregation often involves bringing together different datasets to provide a holistic view. Creating a single dataset from various inputs forms the basis of data aggregation, allowing analysts to work with a unified set of information for analysis.

Filtering data, however, is not inherently a part of the aggregation process. While filtering can precede aggregation (for instance, removing irrelevant records or focusing on a subset of the data), it does not contribute directly to the process of summarizing or consolidating the data itself. Consequently, filtering is more of a preparatory step that may enhance data quality before aggregation occurs, rather than an aspect of the aggregation itself.