Dataset dashboard

The Dataset Page provides a detailed view of each dataset’s health and monitoring information in Soda Cloud. It includes several tabs to help you explore and manage data quality at the dataset level.

Checks tab

The Checks tab displays the results of all checks defined in the dataset’s contract. Checks are grouped by column, with column-level checks nested under their respective columns. Columns with failed checks are automatically expanded so you can spot issues quickly. You can filter the view to show only failed checks and search for specific checks or columns by name for faster navigation and troubleshooting.

Learn more about Data Testing.

Filter checks by attribute

Filtering check results by attribute is currently in private preview. Contact [email protected] to enable it.

The Checks tab displays the results of all checks defined in the dataset's contract. You can filter the checks displayed on this tab by last result, column, check name, or check attribute. This lets you focus on a meaningful subset of your contract; for example, viewing only checks tagged with a specific data layer, domain, or team.

The health score panel updates dynamically to reflect only the filtered checks, showing you a pass/fail rate for that subset. A "Results for this filter only" label confirms the score is scoped to your current filter. You can save collections to track their progress. Note how, in the following example, the health score drops from 70% to 50% when checks are filtered by attribute:

Checks tab with no checks filter - Health score at 70%

Checks tab with checks filters - Health score at 50%

To apply a filter from the Checks tab:

1

Click the filter icon

2

Select a field from the dropdown and choose a value to filter by

You can combine multiple filters to narrow the scope further.

3

Click Save to save a filter as a collection

Checks that have never been evaluated are excluded from filtered results and do not count toward the filtered health score.

Metric Monitors tab

The Metric Monitors tab shows the metrics that are actively monitored for the dataset, helping you track trends and detect anomalies over time.

Learn more about the Metric Monitoring dashboard.

Columns tab - Profiling

The Columns tab provides an overview of the dataset’s structure, including column names, data types, distinct counts, and other statistics. You can search for a specific column by name to quickly locate and review its profiling details.

Scans tab

The Scans tab lists all scans that have been executed for the dataset. This gives you a dataset-level view of what has been scanned, why it was scanned, and what the outcome was.

Typical scan types include:

• Contract verification scans to validate that the dataset matches the expectations defined in its contract.

• Metric monitoring scans that compute and track dataset metrics over time.

• Profiling scans to generate profiling results for the dataset (such as statistics and distribution insights).

From the Scans tab, you can:

• Review the list of all scans related to the dataset.

• Open a specific scan to inspect its details and results.

• Access the scan execution logs to support troubleshooting and root-cause analysis.

Incidents tab

The Incidents tab lists incidents related to the dataset, helping you track issues and collaborate on resolution. You can filter incidents based on criteria such as user lead, status, or severity to focus on the most important or urgent cases.

Learn more about incidents.

Requests tab

The Requests tab displays all contract change requests associated with the dataset. It enables dataset owners and data consumers to collaborate on improving the dataset contract over time.

In the Requests tab, you can:

• Browse all requests for the dataset.

• Search and filter requests by status (such as Open, Done, or Won’t Do).

• Open a request to review and collaborate via:

  • Messages and comments between participants

  • Proposals showing suggested contract changes (including added/modified/removed elements)

This workflow supports structured contract collaboration where consumers can propose changes directly, and dataset owners remain the final decision-makers for publishing updates.

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