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How monitoring and anomaly detection work

No-code tests

Quickly add monitors without writing code

Suggestions and usage icons highlight where to place monitors

Set manual thresholds and use custom SQL for your known issues

Machine learning-based monitors identify unknown issues

View all monitor types

Leverage suggestions and customize to your needs

Configure monitors to find data quality issues within your table’s dimensions

Interact with models directly through sensitivity adjusting and feedback

Tailor monitored data through time windows and 'WHERE' clauses

Group by monitor docs

How monitoring modeling works

Metadata from warehouses used for freshness and volume to limit compute

Deep data sampling queries used to find issues within your data

Sophisticated modeling works within 3 days and accounts for seasonality

Product release post for monitor forecasts
Automated Personalization

Monitor by different dimensions within a table

Monitor business metrics such as average revenue or mean by customer, at scale

Easily select one or more groupings without manually defining them in SQL

Avoid alert fatigue with our automated issue grouping

Group by Monitor docs

Monitor types

Metaplane supports the following types of monitors out-of-the-box, from monitoring row counts and freshness to mean and standard deviation.

Learn more

Row counts

Alerts on-changes to expected volume


Alerts no longer than expected update times


Alerts on new or removed unique values

Nullness / Uniqueness

Alerts on changes to percentage nullness or uniqueness


Alerts on changes to statistical properties like mean, min, max, standard deviation

Custom SQL

Alerts on anomalies for arbitrary SQL queries that return a number

Avoid the Urgent emails, find your data quality issue with Metaplane