Data quality exists only when business users have a consistently high level of confidence in the accuracy, completeness and appropriateness of the data they rely on for running their business, making decisions and delivering product and services to their customers.
When inconsistencies arise, identifying data quality issues is not difficult; identifying and remediating the root cause(s) of the data quality issues is what takes the most time and the most effort.
The Adaptive Metadata Manager and the Adaptive Business Glossary Manager provide the support that effective data governance practices require which, in turn, results in the high quality data upon which business organizations can rely.
Facilitating Enterprise Data Quality through Adaptive’s DQ Assessment Model
Maintaining a perception of “high quality data”, plus establishing a “standard” root- cause identification process, requires a comprehensive, consistent view of the organization’s data assets from both business and technology perspectives. The Adaptive Data Quality Assessment Model (pictured below) provides these perspectives.