Which can you manipulate to make a query activity more efficient?

The filtering dimension is key to making a query activity more efficient because it defines the criteria used to select records from the data source. By carefully choosing the filtering dimension, you can significantly reduce the number of records that need to be processed, which speeds up the query execution time. This means that the system has fewer records to evaluate, leading to faster performance and more efficient resource use.

When you set a filtering dimension that accurately reflects the specific subset of data you need, it ensures that your query runs only on relevant information. This targeted approach minimizes unnecessary workload and can lead to quicker reports and insights, ultimately improving the overall efficiency of your data manipulation processes.

In contrast, while aspects like data source, execution time, and record counts are important considerations, they do not directly influence how the query retrieves and processes data in the same way. The primary driver of efficiency in query processing is how effectively the filtering dimensions are applied.