# What is dashboard reliability? Definition and Examples | Silicon

URL: https://meetsilicon.com/glossary/dashboard-reliability/

> Dashboard reliability is the confidence that a dashboard loads, shows current data and calculates its numbers correctly every time someone opens it.

Reliability fails in three ways: the dashboard errors, the data is stale, or the number is wrong without anyone noticing. The last is the most damaging because decisions get made on it.
## The three ways dashboards fail
Broken dashboards error or show empty charts, usually after an upstream change. Stale dashboards load but show old data because a job failed or ran late. Wrong dashboards load fresh data but calculate it incorrectly, for example after a filter was changed in one chart and not in others.
The first kind gets noticed quickly. The second and third can go unnoticed for weeks, and they are the ones that end up in board decks.
## How teams improve it
Define metrics once so charts cannot disagree, check upstream changes against the content that depends on them before they merge, show when each chart was last refreshed, and review old dashboards so unused ones are archived instead of quietly going stale.
## How Silicon handles it
Silicon checks pull requests against dashboards, builds charts from defined metrics, and runs Autopilot on a schedule to fix broken charts and flag stale or slow content.
FAQ
## Dashboard reliability questions
### How do you measure dashboard reliability? +
Track how often dashboards error, how often their data is older than expected, and how many incidents came from wrong numbers rather than errors.
### Who owns dashboard reliability? +
Usually the data or analytics engineering team, with each metric owned by the team that uses it.
## Related
- Schema drift ->
- Data freshness ->
- What is dashboard reliability? ->
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