The difference between the Elementary column anomaly monitors missing_percent and null_percent is: - null_percent measures the percentage of only null values in a column out of the total number of rows. - missing_percent measures the percentage of "missing" values in a string column, which includes empty strings (''), strings with only spaces (' '), and nulls, out of the total number of rows. So, missing_percent is broader for string columns, capturing both nulls and empty/blank strings, while null_percent only counts actual nulls. This distinction is important when you want to monitor for all types of "missing" data, not just nulls, especially in string columns where empty values can be common [Slack answer on missing vs null percent](https://slack.com/archives/C02CTC89LAX/p1656075987045489).