Configure data quality dimensions

Data quality dimensions categorize data quality findings to help communicate the type of issues detected. They are shown on the Monitors tab of the Job Details page and the Quality tab of Catalog asset pages.

You can use these settings to customize dimension terminology and assignments for your organization.

Before creating custom dimensions, review the out-of-the-box dimensions and their associated monitors.

Out-of-the-box data quality dimensions

Dimension Definition
Accuracy

The degree to which data correctly reflects its intended values.

Monitors associated with the Accuracy dimension: Min, max, and mean values
Completeness

The percentage of cells in a column that contain values identified as actual values, null, or empty. Completeness refers to the percentage of columns that have neither EMPTY nor NULL values.

Monitors associated with the completeness dimension: Row count, null values, and empty fields
Consistency

The degree to which data contains differing, contradicting, or conflicting entries.

Monitor associated with the consistency dimension: Execution time
Integrity

The legitimacy of data across formats and as it's managed over time. It ensures that all data in a database can be traced and connected to related data.

Monitor associated with the integrity dimension: Schema change
Validity

The degree to which data conforms to its defining constraints or conditions, which can include data type, range, or format.

Monitor associated with the validity dimension: Data type check
Duplication

The degree to which data contains only one record of how an entity is identified. Refers to the cardinality of columns in your dataset.

Monitor associated with the duplication dimension: Uniqueness

Create a custom dimension

If the out-of-the-box dimensions don't meet your needs, you can create custom dimensions.

Prerequisites

  • You have the Data Quality Admin global role.

Steps

  1. On the main toolbar, click Products icon → Cogwheel icon Settings.
    The Settings page opens.
  2. Click the Data Quality tab.
  3. Click Dimensions.
    4. The Dimensions page opens.
  4. Click Plus icon Create dimension.
    5. The Create Data Quality Dimension dialog box appears.
  5. In the Data Quality Dimension input field, enter a unique name.
  6. Click Create dimension.
    7. Your custom dimension appears in the dimensions matrix.

Warning If you close the dialog box before clicking Create dimension, the custom dimension is not saved.

Important When you create a new dimension, no monitors are mapped to it.

Map a custom dimension to monitors

After you create a custom dimension, you need to map it to data quality monitors.

Prerequisites

  • You have the Data Quality Admin global role.

Steps

  1. In the row containing your custom dimension, select the checkbox for each data quality monitor you want to map to your dimension. The available monitors include:
    • Schema change
    • Data type check
    • Row count
    • Uniqueness
    • Null values
    • Empty fields
    • Min value
    • Max value
    • Mean value
    • Execution time
  2. Click Save changes.

Tip To delete a custom dimension, click Trash icon on the far-right side of the row containing the dimension. You may need to scroll horizontally to access it.