Criticality indicates how important an asset is to the business — used to prioritize monitoring, alerting, and governance effort toward the assets that matter most.
Use Manual mode when business context outweighs system-derived signals — for example, a regulatory reporting table that’s rarely queried but mission-critical.
How Auto Criticality Is Derived
Criticality is an automatically derived score representing how important an asset is to the business, based on five factors:
Usage carries the most weight, combining how many unique users access the asset with how many read queries it receives — assets used by many people, frequently, score higher.
Dependency is equally weighted with Usage, capturing how many upstream and downstream assets rely on it — the more connected an asset is, the bigger the impact if it breaks.
Metadata completeness contributes a moderate amount, driven mainly by whether the asset has linked business terms and domain/app/product classification, with smaller contributions from tags (whether DQLabs-detected or sourced) and a written description — well-governed assets are treated as more deliberately important.
Freshness and Attribute Criticality play a smaller, supporting role — freshness reflects how recently the asset was updated, while attribute criticality reflects whether the asset contains sensitive or business-critical columns.
Volume has the smallest influence, based simply on row count — larger datasets nudge the score up slightly, but size alone isn’t a strong indicator of importance.
Together, Usage and Dependency dominate the score, which is exactly why low-usage but compliance-critical assets (like a rarely-queried regulatory table) often need a Manual override — the automatic calculation won’t fully capture business-mandated importance on its own. This works well for most assets because criticality often does correlate with how connected or heavily used something is.
When to Use Manual Override
Auto-calculated criticality can miss business context that usage data alone doesn’t capture. Switch to Manual when:
- Regulatory or compliance tables — rarely queried, but legally mandated and high-risk if incorrect (e.g., financial reporting source tables).
- Low-traffic but high-stakes assets — used only during specific events like month-end close, audits, or annual reporting.
- New or recently launched assets — not enough usage history yet for Auto to reflect true importance.
- Strategic initiatives — assets supporting a new business priority that hasn’t generated significant query volume yet.
Why This Matters
Criticality classification drives:
- Alert prioritization — critical assets typically trigger higher-severity alerts on quality issues.
- Review urgency — issues on critical assets get flagged for faster resolution.
- Governance focus — stewards and owners are encouraged to prioritize documentation and monitoring for critical assets first.
Manual override ensures these downstream behaviors reflect actual business risk — not just system-observed activity. 