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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. These packaged solutions help implement and support the practice of data quality assurance, mostly embedded as part of a broader data and analytics (D&A) strategy. Various existing and upcoming use cases include: 1. Analytics, artificial intelligence and machine learning development 2. Data engineering 3. D&A governance 4. Master data management 5. Operational/transactional data quality

• Experian Pandora (Legacy)
  4.0

  25 Reviews
• Experian Aperture Data Studio
  4.4

  62 Reviews
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Reviews for 'Customer Relationship Management - Others'

• Experian
  4.7

  5 Reviews

Reviews for 'Data and Analytics - Others'

• Experian Address Validation Service
  4.6

  8 Reviews

Gartner defines a Data and Analytics Governance Platform as a set of integrated business and technology capabilities that help business leaders and users to develop and deploy a diverse set of governance policies and monitor and enforce those policies across their organizations’ business systems. These platforms are unique from data management in that data management focuses on policy execution, whereas these platforms are used primarily by business roles — not only or even specifically IT roles.

• Experian Aperture Data Studio
  4.0

  1 Review