In Dataflows Query Editor connected to an Azure SQL customer table, which option helps identify which column contains non-duplicate values per customer?

• A. Column Distribution - distinct values
• B. Column distribution - unique values
• C. Column profile - values count
• D. Column quality - valid values

Answer: (A)

Profiling the data to see how many different values appear in each column quickly reveals duplication patterns. The column distribution feature that shows distinct values tells you how many unique values exist for a column across all rows. If a column has as many distinct values as there are rows, every row has a unique value in that column, meaning there are no duplicates for that column across customers. That direct relationship makes it the best way to identify columns with non-duplicate values.

The other options don’t provide the same direct signal. Column distribution that highlights unique values (values that occur only once) is related but focuses on values that appear a single time, which is not as straightforward for assessing overall non-duplication per column. Column profile with values count shows how many values exist but not how they’re distributed or whether duplicates occur. Column quality focusing on valid values checks data validity, not duplication patterns.