Create an Any Not Null Check
Step-by-step tutorial for creating an Any Not Null check across two or more fields on a table or file. For what each property means and how the rule evaluates the data, see the How It Works page.
Permission Required
You need the Author team permission on the datastore to create an Active check, or Drafter to create it as a Draft. See the Permissions page for the full matrix.
Show me how
The app can walk you through this. Click Show me how in the check creation form's header, or press H while it is open, and the Add a Check walkthrough highlights each step while you fill in the real form.
Field reference
The Authored Check Details form is organized in the sections below. Fill them in as you follow the Steps.
Target
| Field | Required | Type | Description |
|---|---|---|---|
| Associate with a Check Template | Toggle | Links the check to a Check Template. Enabling it replaces the Rule Type dropdown with a Template dropdown where you pick an existing template, which then controls the check's properties. When off, you configure everything on this form. | |
| Rule Type | Option | The validation logic to apply. Select Any Not Null for this check. Shown only while Associate with a Check Template is off. | |
| Table / File | Option | The target the check runs against. The label follows the datastore, reading Table on a database and File on a file system. Locked after the check is saved. | |
| Fields | Option | The fields evaluated together. Select two or more; a row passes when at least one of them holds a value. Every field type is accepted. | |
| Filter Clause | Text | A SQL WHERE expression that limits the rows the check evaluates. Rows outside the filter are ignored entirely. |
|
| Custom Anomaly Description | Toggle | Appears under Advanced, at the end of this section, once a table is selected. It uses the value of another field on the violating row as the anomaly message instead of the default one. Enabling it shows an Anomaly Message Field dropdown where you pick that field. When the selected field is empty for a violating row, the default message is used. |
Pass Criteria
| Field | Required | Type | Description |
|---|---|---|---|
| Coverage | Slider | The percentage of evaluated rows that must pass. Defaults to 100%; lower it only when a known fraction of rows is allowed to fail. |
Ownership
| Field | Required | Type | Description |
|---|---|---|---|
| Owner | Option | The user responsible for the check. Already filled in with the check creator. | |
| Anomaly Assignee | Option | The user automatically assigned to anomalies the check produces. |
Metadata
| Field | Required | Type | Description |
|---|---|---|---|
| Description | Text | A plain-language description of what the check enforces. Supports Markdown formatting: click the field to open the Markdown editor. Click the Apply suggested description button for a suggestion based on the rule type. | |
| Tags | Option | Tags applied to the check for filtering and organization. | |
| Additional Metadata | Key-value | Custom key-value pairs, typically links to catalog entries, tickets, or governance records. |
Let AgentQ fill in the form
When AgentQ is configured for your deployment, the Check Assistant panel in the check form can author the check for you: describe the rule in plain language (for example, "every customer needs at least one of email, phone, or mobile") and it proposes a configuration you can apply to the form. Review the filled-in fields, then Validate and Save as usual.
No Properties section
Any Not Null has no rule-specific properties: the rule is fully defined by the selected fields, the filter, and the coverage.
Steps
Step 1: Select the source datastore from the left menu, then click the Checks tab.
Step 2: Click Add in the top-right corner and select Check from the dropdown. The Authored Check Details form opens.
Step 3: Select Any Not Null in the Rule Type dropdown.
Step 4: Fill in the required fields and any optional ones you need. Every field is described in the Field reference above.
Step 5: Click Validate to test the rule against the selected data without saving it. A success message confirms the rule can run on that data. If validation fails, see Troubleshooting.
Step 6: Click Save. A success message confirms that the check was created.