With modern enterprises increasingly relying on real-time analytics, machine learning, and automated decision engines, tolerance for data corruption has dropped to zero. As such, modern data environments require data architecture that not only detects data anomalies in real time but actively mitigates and repairs them without interrupting live data flows...

One of the challenges data warehousing has faced in recent years has to do with the growing volumes of data It has manage. As data volumes have increased, data warehouses find themselves unable to keep up. As a result, organizations are struggling with inconsistent data quality, coupled with the fragmented systems and manual processes that are in place in many of these organizations...