Magic Quadrant for Augmented Data Quality Solutions
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.
Vendors must, among other requirements:
A: This research covers the augmented data quality solutions market, evaluating 12 vendors on their ability to execute and completeness of vision. It assesses vendors' capabilities across must-have functions including connectivity, profiling and monitoring, matching and linking, business-driven workflows, rule discovery and management, data transformations, and unstructured data support. The research analyzes how vendors leverage AI/ML, graph analysis, and metadata analytics to automate and augment data quality processes. It covers both stand-alone data quality products and unified data management platforms that embed data quality features, examining deployment options from on-premises to SaaS.
A: Data and analytics leaders should use this research to evaluate and select augmented data quality solution vendors that align with their organization's specific needs and strategic priorities. It is particularly valuable for organizations looking to support AI adoption, digital transformation initiatives, or modernize their data quality capabilities. The research should be used in combination with the companion Critical Capabilities for Augmented Data Quality Solutions report, Gartner's client inquiry service, and Peer Insights reviews. Organizations should not select vendors solely based on their quadrant position, as Challengers, Visionaries, or Niche Players may be the best fit depending on specific use cases, data domains, industries, or geographic requirements.
A: Mandatory features for vendors in this market include: (1) Connectivity across diverse data sources; (2) Profiling and monitoring/detection with AI-driven recommendations; (3) Matching, linking and merging using AI/ML; (4) Business-driven workflow and issue resolution; (5) Rule discovery, creation and management including ML-supported and natural language-based rule creation. These must all leverage augmentation through AI/ML features, graph analysis, and metadata analytics.
A: Vendors are excluded if they: (1) Are limited to a single application environment, industry, or data domain; (2) Support only limited data quality functionalities without augmentation/automation or address only very specific problems like address cleansing only; (3) Support only on-premises deployment with no cloud-based deployment options on public clouds (AWS, Azure, or Google Cloud); (4) Do not provide cloud-based/SaaS deployment options; (5) Lack cloud-native data quality capabilities and unstructured data support; (6) Are not positioned for general-purpose data quality use cases and require additional components to fully address scenarios.
A: Ability to Execute evaluates vendors on current market performance - the quality and efficacy of processes, systems, and methods that enable competitive, efficient, and effective performance impacting revenue, retention, and reputation. It focuses on present-day capabilities like product quality, viability, sales execution, pricing, marketing effectiveness, customer experience, market responsiveness, and operations. Completeness of Vision evaluates vendors on future direction - covering current and future market direction, innovation, customer needs, and competitive forces. It assesses how well vendors understand and align with Gartner's view of where the market is heading, including market understanding, innovation leadership, marketing/sales strategies, product roadmaps, business models, vertical/industry focus, and geographic expansion plans.