Gartner’s latest Magic Quadrant for Augmented Data Quality Solutions highlights a clear message: data quality has become fundamental to the success of AI initiatives. As organisations lean heavily into automation, analytics and intelligent decision making, the market is shifting rapidly to support AI ready data at scale.
AI is now reshaping the entire data quality lifecycle. It influences everything from rule creation to ongoing monitoring and anomaly detection. AI agents and multi agent orchestration are emerging to help automate and streamline data operations. Natural language processing and large language models have also made data quality tools far more accessible, allowing non technical users to express requirements in everyday language. At the same time, unstructured data has become a key part of enterprise AI strategies, increasing the need for advanced validation and rich metadata generation.
Why Data Quality Matters More Than Ever
Across industries, organisations are accelerating AI adoption, and modern data quality solutions are becoming essential. Gartner notes that by 2027 around 70 percent of organisations will have invested in updated data quality capabilities to support automation and digital transformation.
Reliable data is now central to any AI strategy. High quality data helps build trust in AI outputs and ensures that both structured and unstructured content is validated before it reaches models or analytical workflows. Continuous monitoring and automated remediation across data pipelines are becoming standard expectations, especially as businesses look to shorten the time between data creation and insight delivery.
Fig 1: Magic Quadrant for Augmented Data Quality Solutions
Qlik’s Leadership in Augmented Data Quality
Qlik has once again secured its place as a Leader in the 2026 Gartner Magic Quadrant for Augmented Data Quality Solutions. This repeated recognition reflects Qlik’s commitment to delivering trusted, high‑quality data and preparing organisations for an AI‑driven future.
As data quality becomes increasingly intertwined with AI readiness and real‑time decision making, Qlik stands out through its strong metadata‑driven architecture, advanced AI‑assisted capabilities and global network of skilled partners.
Gartner highlights Qlik’s strong market performance, including a “Rule of 50” score of 53 percent and a 108 percent net customer retention rate. Qlik’s data quality revenue also grew by more than 32 percent, outperforming all other vendors included in the evaluation.
AI‑Powered Data Quality Capabilities
A major strength of Qlik’s offering is its investment in AI to reduce manual effort and improve consistency across data processes. Qlik now provides a GenAI‑powered rule assistant that can automatically suggest data quality rules based on schema and profiling information. It can generate cross‑column logic from natural language inputs, identify root causes of data issues and clearly reference the rules involved. Qlik also automates the creation of metadata descriptions so data stewards can review and refine them more efficiently.
This blend of intelligent automation and human oversight significantly speeds up data quality workflows while improving reliability.
A Metadata‑Driven, AI‑Ready Platform
Qlik’s unified platform applies a strong metadata‑driven foundation that supports data quality, governance and AI‑readiness across hybrid environments. Its patented Trust Score helps organisations understand the reliability of their data assets, allowing teams to make faster, more informed decisions.
Looking ahead, Qlik’s roadmap focuses on expanding AI‑assisted rule generation, enhancing metadata automation, strengthening its Open Lakehouse architecture and delivering contract‑governed data products. It is also building on FinOps‑driven data operations following its acquisition of Upsolver.
All of this points to an exciting future for Qlik as it continues to evolve.
How We Support our Customers
Advancements in augmented data quality are impressive, but organisations often need expert guidance to unlock the full value of their data environment.
That’s where we come in.
We support the entire data ecosystem and help customers make the most of their investment through:
- Data Quality Assessments and Improvement Road Maps
- Data Warehousing / Fabric Solutions
- BI implementation and setup
- Dashboard / report development
- Data modelling best practices
- Ongoing system and tenant management
- Training for users at all skill levels
- Long‑term optimisation and strategy support
If you want to unlock the full potential of your analytics environment, we are here to help.
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