A common reason for "Invalid Date" errors in the Elementary UI, even when the underlying data and timestamps look correct in the graphs, is related to how the timestamp column is configured or handled: - If no valid timestamp column is defined in your test configuration, the UI may display "Invalid Date" as a placeholder. This is a known UI glitch when the timestamp column is missing or not properly set. In such cases, Elementary falls back to calculating metrics on the entire table without time buckets, but the UI still expects a timestamp for display purposes, resulting in "Invalid Date" being shown on the chart axis or in tooltips. This does not affect the underlying data, which is why you still see correct timestamps when inspecting the raw data or graphs more closely [Slack discussion on Invalid Date in UI](https://slack.com/archives/C02CTC89LAX/p1667504828562969). - Another possible cause is if the timestamp column contains null values or is not of the correct type (timestamp or date). This can also lead to display issues in the UI, even if the data itself is present and correct [Anomaly Troubleshooting Guide](https://docs.elementary-data.com/data-tests/anomaly-detection-tests/Anomaly-troubleshooting-guide). In summary, "Invalid Date" in the UI is typically a display issue related to the configuration or presence of the timestamp column, not the underlying data itself. Double-check your test configuration to ensure a valid timestamp column is specified and that the column contains valid, non-null timestamp or date values.

To avoid "Invalid Date" errors in the UI, your test definition should explicitly specify a valid timestamp column in the test configuration. Here’s how you should define it in your YAML file for an Elementary anomaly detection test:

yaml models:   - name: your_model_name     tests:       - elementary.volume_anomalies:           timestamp_column: your_timestamp_column

Replace

your_timestamp_column

with the actual column name in your table that contains valid timestamp or date values. This ensures that Elementary can correctly bucket your data over time and display proper dates in the UI [docs: timestamp_column](https://docs.elementary-data.com/data-tests/anomaly-detection-configuration/timestamp-column). If you do not specify a timestamp column, Elementary will process the entire table as a single bucket, and the UI may show "Invalid Date" due to the absence of time-based grouping [Slack discussion on Invalid Date in UI](https://slack.com/archives/C02CTC89LAX/p1667504828562969). Example for a column_anomalies test:

yaml models:   - name: your_model_name     columns:       - name: your_column         tests:           - elementary.column_anomalies:               timestamp_column: your_timestamp_column               column_anomalies:                 - null_count

Always ensure the timestamp column exists in your model and contains valid, non-null timestamp or date values.

If you are referring to the standard dbt test block (using the

tests:

key in your YAML), the approach is the same for Elementary anomaly detection tests: you define the test under the

tests:

section for your model or column, and you can include the

timestamp_column

parameter directly in the test configuration. Here’s an example of how it should look in a dbt YAML file:

yaml models:   - name: your_model_name     tests:       - elementary.volume_anomalies:           timestamp_column: your_timestamp_column

Or for a column-level test:

yaml models:   - name: your_model_name     columns:       - name: your_column         tests:           - elementary.column_anomalies:               timestamp_column: your_timestamp_column               column_anomalies:                 - null_count

This is the standard way to define Elementary tests within the dbt test block. The key is to ensure that the

timestamp_column

is specified and points to a valid timestamp or date column in your data, as this is required for proper time bucketing and to avoid UI issues like "Invalid Date" [docs: timestamp_column](https://docs.elementary-data.com/data-tests/anomaly-detection-configuration/timestamp-column). If you meant something different by "dbt_test," please clarify your question.