Augmented Data Quality Solutions

Augmented data quality uses machine learning and automation to profile data, suggest and enforce rules, detect anomalies and fix issues, reducing manual rule writing.

Frameworks such as Great Expectations are code-first libraries for tests you write, while augmented solutions are broader platforms that discover rules, remediate data and report to business users.

Common dimensions are accuracy, completeness, consistency, timeliness, validity and uniqueness.

Matching, de-duplicating and mastering records improves quality, so master data management tools such as Tamr, Profisee and CluedIn are often bought together with data quality platforms.

Qlik, Precisely, SAS and CluedIn now point to their specific product pages instead of home pages, and Talend's data quality pages now live under Qlik.

The section 'Open Data Quality Tools' lists Great Expectations, Soda, Deequ, Pandera, dbt Data Tests.

The 2026 Magic Quadrant for Augmented Data Quality Solutions is dated 11 February 2026 in IBM's citation, and Qlik says Gartner evaluated 13 vendors. Ataccama (fifth consecutive Leader placement, ranked first for Completeness of Vision), Salesforce's Informatica (18th time), Qlik (seventh year) and IBM each say they were named Leaders; the other vendors' placements could not be confirmed. Ataccama's summary says AI assistants are now formally evaluated, innovation explicitly covers generative and agentic AI automation, alerts and visualisation are a mandatory capability, unstructured data scope adds graph technologies for relationships between extracted entities, and "AI/ML development" is renamed "Analytics and AI readiness".