Input Validation for Domain Tables

We're adding a new capability to help drive higher quality data in Amperity and throughout your ecosystem - . This feature introduces a series of validations that provide measures of data quality for columns tagged with a given semantic, alerting on data anomalies and helping diagnose common data quality issues. We have an initial list of validations and will be expanding to include more over time. This initial release gets us closer to continuous data quality monitoring and observability from ingest through to activation.

Source data quality issues cost you time and money. They slow down implementations and they can cause significant problems with activation and analytics. They need to be identified as quickly as possible. Today, even when an issue is found, manual querying and investigation are needed to identify the origin. Input Validation makes it much easier to identify those source issues and, more importantly, get them fixed quickly. This new feature should save you time managing data quality and analytics, but also lead to better outcomes from campaigns.

To use :

We’ll continue to add not only new data quality measures, but new data quality frameworks as well, including run-over-run comparisons and more advanced measures of data quality assessment. We also plan to implement thresholding, alerting, and workflow impacts in the future.