Code-based tests take hours to write and maintain, so it's hard to achieve the coverage you need.
In Metaplane, you can add hundreds of tests within minutes. We support foundational tests (e.g. row counts, freshness, and schema drift), more complex tests (distribution drift, nullness shifts, enum changes), custom SQL, and everything in between.
Manual thresholds take a long time to set and quickly go stale as your data changes.
Our anomaly detection models learn from historical metadata to automatically detect outliers. Monitor what matters, all while accounting for seasonality, trends, and feedback from your team to minimize alert fatigue. Of course, you can override with manual thresholds, too.
Knowing about an issue is only half of the battle. Do executives use this data every day, or has it not been accessed in the past quarter?
Metaplane automatically establishes lineage from data in your warehouse to the dashboards used by your stakeholders. Understand downstream impact, prioritize work, and get in touch with the right people. If you use dbt, we'll pull in that metadata too.
You don't know when silent data bugs occur.
Metaplane notifies you of issues immediately in Slack/PagerDuty/e-mail. Mark any alert as an expected change and Metaplane will learn over time. Watch conversations develop as your team's awareness of data issues increases.
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.