The correct answer is D. The volume of the data .
The NULL_COUNT Data Metric Function returns the number of NULL values in a column. This type of metric is used to verify data quality by measuring the amount, or volume, of missing values.
Why D is correct:
NULL_COUNT counts how many rows contain NULL in a specified column. Since it produces a count, it is used to evaluate the volume of missing data.
Example concept:
SELECT SNOWFLAKE.CORE.NULL_COUNT(
SELECT column_name FROM my_table
);
This returns the number of NULL values found in the selected column.
Why the other options are incorrect:
A). Accuracy verifies whether data values are correct, but NULL_COUNT only counts missing values.
B). Uniqueness is verified with metrics that check duplicate or distinct values, not NULL_COUNT.
C). Freshness measures how current or recent the data is, not how many nulls exist.
Official Snowflake documentation reference:
Snowflake documentation describes NULL_COUNT as a system Data Metric Function that returns the number of NULL values in a column.
Reference: Snowflake Documentation - Data Metric Functions; Snowflake Documentation - SNOWFLAKE.CORE.NULL_COUNT; SnowPro Core Study Guide - Data Protection and Governance.
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