The data quality function of a data governance practice focuses on data quality’s dimensions of completeness, validity, uniqueness, consistency, integrity, and timeliness. It represents these to the Data Governance Office in a way that allows for the data to be evaluated for exposure to data quality issues, from both the technical and business perspectives.
If cars can drive themselves, why can't data management? Artificial intelligence can now facilitate the classification and processing of metadata, leading to remarkable gains in efficiency, quality and speed. Find out more in this webinar.
Trusting your data means understanding its lineage. We’ve recently announced a partnership with MANTA to enrich our ‘self-driving’ data management platform with data lineage and bring its capabilities to both business and technical users.
Watch this webinar to learn how to maintain reference data centrally and improve data governance with a single version of truth, and why Excel is not the right tool for this.
Data Quality Management doesn't have to be rocket science. Replay our 30-minute webinar to see how you can deploy a DQ monitoring solution from your browser in a matter of days.
Watch this webinar to learn why managing metadata is important, how to get started, how to operationalize metadata for business applications, and why AI is becoming critical for metadata management.