Absolutely! 

The shift to agentic, usage-aware monitoring is a game-changer for data engineers who've spent years drowning in false alerts while critical issues slipped through.

By combining Unity Catalog's lineage with intelligent impact scoring, we finally prioritize what actually matters: high-downstream-dependency tables that power dashboards, models, and reports.

That dashboard view you shared is exactly what we've needed — unhealthy tables surfaced by severity, clear root causes (stale jobs, incomplete runs), and scan frequency tuned to real usage patterns.

No more blanket freshness rules on rarely-queried tables.

I'm thrilled to see this in public preview. It directly addresses the feedback we've heard for years: data quality should reduce toil, not add it.

Curious — what's the biggest data quality pain point this solves for your team? False positives?