Which functionality allows data to be consolidated across multiple rows for easier analysis?

The functionality that allows data to be consolidated across multiple rows for easier analysis is "Group by." This feature is commonly used in data analysis to aggregate data points based on a specified dimension. When employing "Group by," you can summarize data in various ways, such as calculating the sum, average, count, or other statistical measures for each group.

For instance, if you have a dataset containing sales transactions, using the "Group by" functionality allows you to consolidate all sales related to a particular product or date into a single entry that displays the total sales amount or count. This makes it easier to analyze trends and insights by providing a summarized view instead of working with individual transactions.

The other options serve different purposes: "Filter" narrows down the dataset to specific criteria without aggregation, "Join" combines multiple datasets based on a common field but does not perform aggregation on multiple rows, and "Unpivot" transforms columns into rows to normalize data structures, which is not meant for aggregation. Therefore, "Group by" is the functionality specifically designed for data consolidation across multiple rows.