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 data quality with minimal issues (Green)
70-89%:
Good quality with some attention required (Yellow)
Below 70%:
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.
Navigate to the Alation Data Quality application and click Monitors.
Filter monitors by Status using the dropdown to view All Monitors or only Monitors with Failures.
(Optional) Search by a monitor name or sort by quality score, failure count, or last execution time.
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.
Navigate to the Alation Data Quality application and click Assets.
Search for specific tables using names or sort either by data quality score or by number of failed checks.
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 |
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