Bad data caught before it costs you.
Doe runs SQL-based quality checks against your database every 6 hours: sync freshness, row counts, null rates, schema drift. Every check is a readable SQL assertion. Alerts fire with the exact table, column, and threshold that failed.
Doe monitors data quality across your Postgres and MySQL databases every 6 hours. Connects to Neon, Supabase, and PlanetScale. Checks sync freshness, row counts, null rates, and schema drift using SQL assertions you can read and edit. Alerts fire with the exact table, column, and threshold that failed, before bad data reaches dashboards or downstream systems.
What changes
| Dimension | Before | With Doe |
|---|---|---|
| Detection timing | When someone sees wrong numbers in a dashboard | Within hours, before downstream systems consume it |
| Investigation time | Half a day figuring out whether the data, the sync, or the query is broken | Alert includes the exact table, column, check SQL, and likely root cause |
| Pipeline coverage | Fivetran/Airbyte show sync status, but not whether the data is correct | Row counts, null rates, and freshness validated at the destination |
| Schema changes | Break downstream queries silently for days | Detected and flagged before dependent systems are affected |
How Doe monitors your data quality
Neonstripe_subscriptions is 18 hours stale (expected < 2 hours). Null rate on customers.plan_id spiked from 0.1% to 12%. A new nullable column was added to the orders table since the last snapshot
Doe grouped the 3 findings by severity: the stale sync is critical (revenue dashboard affected), the null spike is high (downstream funnel query will under-count), the schema change is informational. Failed SQL assertions included for each
The revenue dashboard says $0 for yesterday. Nobody noticed until the CEO did.
Your Stripe data syncs to Postgres via Fivetran. PostHog events land on a nightly job. When the pipelines are healthy, everything works. But the Fivetran sync hung at 2 AM because Stripe rate-limited the API. The reporting table is 18 hours stale. The revenue dashboard shows $0 for yesterday. The CEO screenshots it at 9:15 AM.
Last month it was a schema migration. Someone added a nullable column to the customers table. A downstream query that filters on that column started silently excluding every row where the new field was null. The signup funnel showed a 40% drop. Two people spent a full day investigating the "conversion crisis" before someone realized the data was wrong, not the signups. It had been wrong for six days.
Get started in under 10 minutes
Connect your tools
One-click OAuth for each integration. No API keys, no engineering.
Describe what you need
“Monitor the orders, users, and events tables every 6 hours. Flag anything with more than 5% nulls in required columns or row counts that drop more than 20% from the 7-day average.”
It runs on schedule
Checks run every 6 hours and you only hear about it when something breaks.
Data Quality Monitor FAQ
Sync tools tell you whether the job ran. Doe tells you whether the data is correct at the destination. A Fivetran sync can complete successfully while delivering partial data due to rate limits or schema mismatches. Doe validates actual row counts, null rates, and freshness in your database.
Stop doing the work your tools should do for you.
Set it up once. Doe runs it every time.
