Adobe Analytics Business Practitioner Practice Exam 2026 – The All-in-One Guide to Achieve Certification Success!

The use of the Approximate Count Distinct function is suitable for creating a calculated metric that records the number of unique products viewed at least once over a week. This function is designed to count distinct values within a specified time frame, which allows businesses to get an accurate representation of unique product interactions without double-counting any views that occur multiple times for the same product.

In the context of measuring product views, if the goal is to identify how many distinct products were viewed by users at least once in a given week, employing this function is effective. It provides insights into product engagement and helps assess the diversity of interest among viewers during that period. This ability to capture unique interactions is vital for strategic analysis and marketing efforts.

Other methods such as Row Count or Cumulative Row Sum would not provide an accurate reflection of distinct views as they either count all instances or sum up values without considering uniqueness. Similarly, the Sum of Views would aggregate all view counts together but would also lead to inflated numbers by not distinguishing between unique products. Thus, the use of Approximate Count Distinct is particularly advantageous in this scenario.