Manual tests take hours to write and maintain, so it's hard to achieve the coverage you need.
You can add and monitor hundreds of tests within minutes in Metaplane, from foundational tests to custom SQL and everything in between.
Manual thresholds create alert fatigue, then quickly go stale as data changes.
Metaplane's monitors learn from historical metadata to detect anomalies while accounting for seasonality, trends, and feedback from your team.
Knowing about an issue is only half of the battle.
Metaplane extracts lineage from databases to dashboards so you can assess downstream impact, prioritize work, and notify the right people.
You don't know when silent data bugs occur.
Get notified of incidents immediately in Slack/PagerDuty/e-mail. Metaplane groups together related issues into Incidents, then learns over time as you interact with alerts.
We expose a lot of data and dashboards to our executive team. It really erodes trust when an exec catches a data quality issue—one that we may not have even known existed—and has to call me out on it. Since we installed Metaplane, the number of callouts over bad data has dropped to near zero.
Metaplane alerts us to problems that would otherwise have gone undiscovered until much later. Before now, we've never had a practical way to monitor the hundreds of tables in our warehouse, and we'd learn something was wrong when a business user informed us. Metaplane is exactly the monitoring tool that was missing from our toolbox.
With Metaplane, we have visibility into the health of our data across our infrastructure, from data ingestion and transformation in Snowflake to job run times with dbt to where this data is then referenced in Mode reports. After setting up the platform in only half an hour, we get actionable alerts when things go wrong, with the context needed to debug.
Metaplane gives me peace of mind, knowing that I'll be alerted to events that can impact the business. It's like having a QA Engineer on the team monitoring our data reliability.
Before Metaplane, I might not find out about critical data bugs for weeks—if at all. I routinely find out about issues as they’re occurring, and surprise teams with the speed and scope of what we’re monitoring.