Data Lakes support analytics which will ultimately drive actions which increase revenue, support compliance, prevent churn, etc. However, whether that action is near to real-time or not, none of those can be performed without first performing a DQ check. For example, can you trigger an action before first checking the “GDPR Remove” list? A Data Quality check must always be the first step in any action. OwlDQ with Schema Learned can perform 100+ owl checks. However beyond simply those checks, it is OwlDQ's unique Spark-based architecture listed below that enables innovation. Churn, credit check, AML, infosec checks developed in the Data Lake could be added as part of Owlcheck on the streaming data.