> For the complete documentation index, see [llms.txt](https://docs.collibra.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.collibra.com/data-quality-self-hosted/core-concepts/findings/data-quality-monitors/shapes.md). # Shapes The Shapes monitor detects rare or inconsistent data formats in string columns. Collibra DQ uses a sampling of the metadata to detect potential data issues, which can then be drilled into by creating queries from the data model finding. {% hint style="info" %} The sampling of metadata may change and the number of shapes returned may differ. {% endhint %} The following table shows the information available on the Shapes tab of the Findings page.

Column	Description
Column	The column where Collibra DQ detects a shape.
Schema	The datatype schema of the column where Collibra DQ detects a shape.
Shape	The format of the shape.
Count	The number of times a particular shape format appears in a column.
Row Count	The number of rows in the table, file, or view where Collibra DQ detects shape issues.
Percent	The percentage a shape conforms to the format that Collibra DQ identifies as normal.
Shapes/Col	The number of shape issues in a particular column.
Status	Lets you label and train a finding. The available dropdown menu options are Validate, Invalidate, and Resolve. Validate instructs Collibra DQ to either assign a finding to a specific user for review, which then appears in the View the Assignment Queue or acknowledge without an assignee that the finding is a valid observation. Invalidate instructs Collibra DQ to ignore a finding and allow the value to pass. There are two invalidation options: Save lets you mark a finding as invalidated. Save & Retrain lets you invalidate a finding and any previously saved invalidated findings, if any. When you have many findings to invalidate, it may be best to use the Save option to invalidate them at the same time, once all findings are reviewed. Resolve Instructs Collibra DQ to mark the finding as an observation and prevents it from appearing in future runs. Resolving a finding does not immediately affect data quality scores.
Profile	The user account that is assigned to this shapes finding. When the Status is Assigned, a user profile displays in this column. When a shapes finding is unassigned, the profile column is empty.
Action	In Pushdown mode, you can download either a CSV or JSON file containing details of the break records. This column does not display for DQ Jobs created in Pullup mode.

### Exporting shape records There are two options above the drill-in table to export the details of your outlier records as .xlsx files: * **Export** generates an Excel file with the details from the drill-in. * **Export with Details** generates an Excel file with the details from the drill-in and the data preview, when available. ### Configuring manual options You can configure additional shape options on the Findings page. Click the

above the upper-right corner of the Shapes Findings table. The following table shows the available options. | Option | Description | Default Value | | --------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------- | | **Occurrence % < \[X]** | Only shows shapes below the given percentage threshold. | 0.001 | | **Format per Col < \[X]** | Only shows columns with less than the given number of formats. For example, when there are 30 formats and the Format per Column value is set to 5, then only 5 columns display. | 20 | | **Character Length < \[X]** | Only shows Shape issues with fewer than the given number of characters. For example, if the value is set to 9, then all values less than 9 will show. | 12 | ## Retrain Updates the DQ models used for automated data-quality checks. The Retrain process consumes current training data (and optionally labels/config), builds a new model or rule-set, validates it, and publishes a new version that will be used to score incoming data and compute DQ metrics. Use **Retrain** when data distributions change, new labels/ground truth are available, business rules change, or on a scheduled cadence to prevent model drift.