Gartner defines augmented data quality (ADQ) solutions as a set of capabilities for enhanced data quality experience aimed at improving insight discovery, next-best-action suggestions and process automation by leveraging AI/machine learning (ML) features, graph analysis and metadata analytics. Each of these technologies can work independently, or cooperatively, to create network effects that can be used to increase automation and effectiveness across a broad range of data quality use cases. These purpose-built solutions include a range of functions such as profiling and monitoring; data transformation; rule discovery and creation; matching, linking and merging; active metadata support; data remediation and role-based usability.
Reviews for 'Data and Analytics - Others'
Master data management (MDM) is a technology-enabled business discipline where business and IT organizations work together for the uniformity, accuracy, stewardship, semantic consistency and accountability of enterprises’ shared master data assets. Organizations use MDM solutions as part of an MDM strategy, which should be part of a wider enterprise information management (EIM) strategy. An MDM strategy potentially encompasses management of multiple master data domains (e.g., customer, citizen, product, “thing,” asset, person/party, supplier, location, and financial master data domains). Data and analytics (D&A) leaders procure MDM tools for data engineers or less-technical users, such as data stewards.