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06/11/2025, 2:54 PMtest_null_count ?kapa.ai
06/11/2025, 2:54 PMkapa.ai
06/11/2025, 2:54 PMnull_count in Elementary, you can use either the elementary.column_anomalies or elementary.all_columns_anomalies test in your dbt model's YAML file. The null_count monitor checks for the number of null values in a column. Example using elementary.column_anomalies on a specific column: yaml models: - name: your_model_name columns: - name: your_column_name tests: - elementary.column_anomalies: column_anomalies: - null_count Example using elementary.all_columns_anomalies for all columns in a model: yaml models: - name: your_model_name tests: - elementary.all_columns_anomalies: column_anomalies: - null_count You can also specify a timestamp_column at the model level if you want the test to be evaluated over time buckets (e.g., daily): yaml models: - name: your_model_name config: elementary: timestamp_column: your_timestamp_column columns: - name: your_column_name tests: - elementary.column_anomalies: column_anomalies: - null_count The null_count monitor is supported for any column type and can be combined with other monitors as needed. For more details and configuration options, see the official documentation on [column anomalies](https://docs.elementary-data.com/data-tests/anomaly-detection-tests/column-anomalies) and [all columns anomalies](https://docs.elementary-data.com/data-tests/anomaly-detection-tests/all-columns-anomalies) tests.