6 Pillars of Data Quality and How to Improve Your Data
See how data quality encompasses various aspects, including accuracy, consistency, completeness, reliability, uniqueness and relevance.
The worst data incident is the one you don’t know about. Data anomaly detection removes any bad data surprise by automatically detecting deviating behavior in your data pipelines and datasets.
Databand uses automated anomaly detection, so you aren’t surprised when pipelines take too long or data values change unexpectedly.
Eliminate the unknown by seeing trends & detecting anomalies from your metadata in real-time.
Set alerts to trigger when unexpected data deviates from expected baselines immediately.
Monitor and detect anomalies 24/7 so you know the data is always delivered accurately.
Databand centralizes your pipeline metadata and analyzes it with ML-powered detection so you can continuously monitor data anomalies.
With anomaly detection, you get alerts on custom or out-of-the-box metrics around pipelines and datasets when they cross a certain threshold.