Continuous Improvement • Prevention
Data stored in databases, file systems, or even within the same file can become inconsistent over time resulting in a degradation in quality and accuracy. This could happen for a variety of reasons including technology changes, merging of data from multiple organizations, migration projects, application bugs, miscommunications between team members, etc.
Edaptive applies a proprietary process - a combination of automatic validation (algorithms based on Artificial Intelligence) and manual review - to identify these inconsistencies and anomalies which could have a critical impact on your end users and their trust in your data. Edaptive has worked with a variety of data, from SGML to data warehouses, and can find issues which you may not be aware of. As an example, Edaptive was able to identify a data issue that had been present but unidentified for 7 years for one client!
Contact Edaptive today to discuss quality assurance options to help prevent and preserve the quality and integrity of your data.