Data Quality Dashboard

Alation Cloud Service Applies to Alation Cloud Service instances of Alation

For instructions on accessing the dashboard, see Access the Data Quality Features The Overview section of the Alation Data Quality dashboard displays the overall health scores of your monitored data assets based on the AI-recommended, manual checks, or custom-created checks either using SQL or common table expressions (CTE) logic.

The dashboard displays the following components:

Data Quality Score

The Data Quality Score helps you prioritize remediation and build trust in your governed data assets. It reflects the overall quality of monitored data across your catalog. It provides a quick overview of how many quality checks are passing successfully and is updated daily or weekly as scheduled to reflect the most up-to-date quality status.

A higher score indicates better data quality and fewer issues detected, while a lower score highlights potential data reliability concerns that may require attention.

The Data Quality Score is designed to help you quickly assess whether data meets expectations across multiple quality dimensions like completeness, uniqueness, validity, and freshness.

The quality score appears on the following pages:

  • Catalog pages

  • Data Quality dashboards

  • Alation Chrome Extension

The health score is an indicator of the number of active checks that have passed over the total number of enabled active checks indicating the following:

  • Executed checks include only those with results of pass or fail.

  • All checks contribute equally.

Score Calculation

Health Score = (Number of Passed Active Checks / Total Number of Enabled Active Checks) x 100

Score Interpretation Guidelines

  • 90-100%: Excellent Excellent data quality with minimal issues (Green)

  • 70-89%: Good Good quality with some attention required (Yellow)

  • Below 70%: Poor Poor quality requiring immediate attention (Red)

Example

Consider tables customer_profiles and orders with 5 data quality checks:

Table

Check

Result

customer_profiles

missing_percent(email) < 2%

Fail

customer_profiles

duplicate_count(customer_id) = 0

Pass

customer_profiles

freshness(updated_at) < 1d

Pass

orders

row_count > 1000

Pass

orders

invalid_count(phone) = 0

Pass

Data Quality Score = (4 / 5) x 100 = 80%

To determine action, consider the following:

  • Warning or Medium Score (75-89%): Some checks have failed

  • Failing or Low Score (<75%): Significant issues are detected in the monitored data

  • 0% Score: All checks have failed and requires an immediate review

View the Data Quality Score Card

The Data Quality Score Card shows a breakdown of the overall data quality Health Score by metric. Each metric includes a pass rate of the relevant checks and a trend graph to show how score changes over time. This card helps you identify which data quality dimensions are weakest and how they’re improving.

You can view the data quality score card for all the assets on the dashboard.

This table lists all the metrics used in the score card with descriptions:

Metric

Description

Timeliness

Checks related to data freshness

Uniqueness

Duplicate or unique value validations

Accuracy

Logical/business rule compliance

Completeness

Non-null or required field validation

Validity

Format/pattern checks

Consistency

Stable schema or values across datasets

Custom

CTE or SQL checks tailored to business

View All Monitors

Users can access comprehensive monitor administration through the Monitors tab.

The Monitors page provides a searchable and filterable view of all existing monitors.

  1. Navigate to the Alation Data Quality application and click Monitors.

  2. Filter monitors by Status using the dropdown to view All Monitors or only Monitors with Failures.

  3. (Optional) Search by a monitor name or sort by quality score, failure count, or last execution time.

  4. To understand which monitors require the most attention, review the following options based on the data quality score for each monitor:

Field

Description

Monitor Name

A unique name identifying the monitor.

Tables Monitored

The number of tables included in the monitor.

Data Quality Score

The calculated health score based on active check outcomes on each monitor.

Checks Count

Total number of checks configured in the monitor.

Checks Failed

Number of checks that failed in the most recent run.

Status

Overall status based on check failures such as pass or fail.

Last Run / Next Run

Timestamps of the previous and upcoming scheduled monitor executions

Created By

The user who created the monitor.

For more information, see Manage Monitors.

View Failing Monitors

The Failing Monitors section provides a quick view of monitors that have one or more failed checks in their latest run. This summary helps in quickly identifying and prioritizing remediation of data quality issues.

This table lists monitors with failed checks from their most recent execution.

Column Name

Description

Monitor Name

Clickable link to the specific monitor’s detail page

Assets Monitored

Number of tables included in this monitor

Checks

Total number of active checks in the monitor

Status

Result of the latest monitor run (e.g., Fail)

Failure Rate

Percentage of failing checks from the last run

Last Run

Timestamp of when the monitor was last executed

Next Run

Timestamp of the next scheduled execution

Interpret Failure Rate

The Failure Rate represents the proportion of checks that failed in the most recent monitor run.

This is calculated as:

Failure Rate = (Number of Failed Checks / Total Checks in Monitor) x 100

Example:

A monitor with 6 total checks and 4 failures will show:

Failure Rate = 66.67%

View Assets

This section provides a centralized view of all data assets currently under quality monitoring.

  1. Navigate to the Alation Data Quality application and click Assets.

  2. Search for specific tables using names or sort either by data quality score or by number of failed checks.

  3. To understand which assets require the most attention, review the following options based on the data quality score for table:

Field

Description

Table

Name and source path of the monitored table

Data Quality Score

Health score based on all checks across the table

Columns Monitored

Number of columns in the table with at least one data quality check

Monitors (Count)

Number of different monitors the table is part of

Checks (Count)

Total number of checks applied to this table across all monitors

View Details

Link to access full table detail page with check results, history, and configuration

  1. Click View Details to get detailed information about the defined checks, observed values against each check, status, and status messages.

View Data Quality Checks

Each check returns one of three results over a scheduled period:

  • Pass: Click to see which values fall within configured thresholds.

  • Fail: Click to see which values exceed thresholds

  • Error: Click to see which checks could not execute