Coverage Initiation:
Anomalo automates data observability for data quality through unsupervised methods

   
The desire for automation is a fact of modern data management, whether it be data integration, metadata management, data quality, or other related initiatives. The current adoption of AI and machine learning suggests this reality.

 Anomalo is looking to package that automation – specifically, unsupervised learning – via its offering to help build a data quality and observability layer for the modern data stack so that issues can be detected and remediated before they become problems in downstream enterprise data consumption.

 This solution can be augmented via low- and no-code options that can be layered on top to guide the best fit for specific business use cases.