Anomalo
Automatically detect data issues and understand their root causes, before anyone else
Solution Designations
Google Cloud Ready
Anomalo helps Google BigQuery customers trust the data they use to make decisions and build products. The partnership provides customers with a way to monitor the quality of the data in any table in BigQuery’s platform without writing code, configuring rules or setting thresholds.
Today’s modern data-powered organizations are using the BigQuery data warehouse to perform real-time, predictive analytics on their centralized data and build and operationalize machine learning models at scale. However, dashboards and production models are only as good as the quality of the data that powers them. Many data-powered companies quickly encounter one unfortunate fact: much of their data is missing, stale, corrupt or prone to unexpected and unwelcome changes. As a result, companies spend more time dealing with issues in their data rather than unlocking that data’s value.
Anomalo addresses the data quality problem by monitoring enterprise data and automatically detecting and root-causing data issues, allowing teams to resolve any hiccups with their data before making decisions, running operations or powering models. Anomalo uses machine learning to automatically assess for a wide range of data quality issues, including deep data observability that learns when there’s an unexpected trend or correlation inside the data itself. This is in contrast to legacy approaches to monitoring data quality that require extensive work writing data validation rules or setting limits and thresholds. If desired, enterprises can fine-tune Anomalo’s monitoring using no-code key metrics and validation rules or by defining any custom SQL check.