DQLabs has been recognized in the Gartner Market Guide as one of 20 vendors. We are listed in all the 5 use cases mentioned in the report.
DQLabs the provider of PRIZM, which is an Enterprise Platform for Data Observability, Data Quality and Context, announced it has been named a Representative Vendor in the Gartner Market Guide for Data Observability Tools (February 2026). We believe the recognition is based on the capabilities of the PRIZM platform by DQLabs.
In the Market Guide, Gartner states that data observability capabilities have gone from being a nice-to-have feature into a tactical necessity. According to Gartner’s 2025 State of AI-ready Data Survey, 53% of D&A or AI leaders said their organizations have already implemented data observability tools. In addition, 31% of respondents claimed they consider implementing the tools within 6-12 months, and 12% within 12-18 months, underscoring near-term momentum. Also, based on Gartner market share analysis, the overall revenue growth in the data observability market is 20.8% in 2024 and comes to $346.4 million. From these data points, Gartner sees strong growth for data observability adoption in the next few years due to the demand for AI-ready data. Gartner identifies the defining market trend as a move toward unified platforms. In the report, Gartner notes: “The market trend is moving toward unified platforms that combine various observabilities, data governance, and security into a single pane of glass. This integration will simplify operations, reduce costs associated with tool sprawl, and improve overall system reliability.”
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“We believe this recognition reflects our vision: that data teams should not have to stitch observability, data quality, and context together from separate point tools,” said Raj Joseph, CEO at DQLabs. “PRIZM was built to unify them on one AI-native control plane, so teams can move from detecting an issue to understanding its root cause and resolving it without switching tools with full context and complete automation. We believe being recognized by Gartner and being mentioned in all five observation categories, including cost allocation, validates that direction for us.”
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How we believe PRIZM by DQLabs goes beyond basic data observability:
- PRIZM by DQLabs mentioned in the all five observation categories Gartner defines: data content, data pipelines, data infrastructure, data lineage and cost allocation.
- PRIZM by DQLabs clusters the alerts instead of creating noise. PRIZM groups thousands of related alerts into a handful of root causes using context, so teams fix few high priority problems to solve thousands of alerts.
- PRIZM by DQLabs observes what matters most. PRIZM scores each asset, attributes, alerts by criticality and puts the deepest monitoring there, rather than treating every table the same and flooding teams with low-value alerts.
- PRIZM by DQLabs observes cost and usage, not just data health. PRIZM tracks query and resource consumption and ties data issues to spend.
Several customers deploying PRIZM by DQLabs report consolidating three or more separate tools into a single platform, recognizing value within the first three months, and completing root cause analysis in minutes rather than days. Because PRIZM clusters alerts to their root cause and automates checks that teams used to build by hand, customers report substantial savings, with fewer people tied up triaging alerts and data engineers freed to build pipelines and data products instead of firefighting.
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