With Destinations, you can analyze the data caught by the filter at a later stage, in a tool of your choice. For example, you can integrate an anomaly table into your data pipelines with automatic jobs to quarantine bad datapoints.
Validio supports a range of destination integrations with different cloud providers, Data Warehouses, and Data streams.
We want to make Validio the world’s best Deep Data Observability platform, and would love your feedback. Let us know at [email protected].
All egress tables from Validio follow the same schema, regardless of which Source the data is validated from.
Validio only writes out datapoints caught by the filter to your destination.
|Auto generated unique identifier of the anomaly.
|Timestamp of when the anomaly was caught.
|True for all egressed points.
|Which filter(s) are applied and whether the filter labeled the datapoint an anomaly.
|The specific datapoint in questions containing all the field values.
One datapoint can be evaluated by multiple filters, such as on different data fields. As long as one of the filters labels the datapoint as an anomaly, the point is egressed.
The JSON egressed in the
_validio_applied_filters lists all applied filters along with a Boolean value that corresponds to whether the filter evaluates the datapoint as an anomaly or not.
You can find the
validator_id in the URL when navigating a specific Validator in the platform.
Updated 9 months ago