By collecting e-commerce data for a specific purpose, you can apply calculations across different business metrics such as abandoned carts, orders placed from a specific city and so forth,  and then use the resulting high-level summary information to present overall statistics of your business. This will help you to draw new insights and relationships in data which you can further use to boost your business performance.

The Aggregation feature can serve this purpose effectively and allows you to perform aggregation operations such as average, max, min, count and cardinality on a given data stream which process the data records and generate the computed results as events for the new output stream. You can also groupby on different attributes.  Apart from that, you can also apply the top-K query which will return top ‘k’ (user-specified integer) values of the chosen attribute.

Average Calculates the running average of the selected attribute.
Count Counts the rows in a specified stream.
MIN Gets the minimum value of the selected attribute over time.
SUM Calculates the sum of values over time.
MAX Gets the maximum value of the selected attribute over time.
Cardinality Calculates the number of unique values of the selected attribute.