DQLabs

Reactive #monitoring creates a false sense of control across thousands of pipelines. No context. No criticality. No way to tell if a failing table feeds a regulatory report or a sandbox notebook. PRIZM by #DQLabs transforms metadata into context, context into criticality, and criticality into autonomous action. ML-driven #anomalydetection, alert clustering, and AI-assisted rule creation shift teams from firefighting to stewardship. In financial services, #observability catches issues at 1x cost instead of 100x impact. This eBook shows you how! https://lnkd.in/gQds3D4P #DataObservability #FinancialServices #DataQuality #PRIZM

Day 1 at Gartner Data & Analytics Summit London and Booth 316! We are on-site to connect with data leaders, stewards, and engineers. Stop by Booth #316 to experience self-driving data observability, quality, and context. - See PRIZM in action. - Meet our experts. - Learn why data leaders are exploring PRIZM. We also have a speaking session today in Theatre 1 at 5:10 PM. Don't miss our Field CTO session: PRIZM by DQLabs, The AI-Native Platform for AI-Ready Data. #GartnerDA #DataQuality #DataObservability #DataContext #PRIZM Venkatesh Perumal Cristina Morandi Steve Spitz Keyur Tripathi

Meet us at Big Data and Analytics Summit at June 9 -10 in Toronto. See PRIZM in action — the industry’s first AI-native platform that unifies data observability, quality, and context into one autonomous system. Discover how leading data teams are moving from reactive monitoring to AI-driven intelligent data operations with PRIZM by DQLabs. Schedule a meeting -- https://lnkd.in/g8Px_FG2 #BigDataSummitCanada #DataObservability #DataQuality #PRIZM

PRIZM World Tour - Minneapolis. May 21 at 5.15 PM DQLabs and YASH Technologies are hosting an evening of baseball, networking, and smarter AI decisions. Private suite at the Saint Paul Saints game. A quick session on how enterprises are making data trustworthy at scale with PRIZM, then we let the conversation and the game take over. Limited seats. https://lnkd.in/dTrtP7pM #PRIZMWorldTour #DataObservability #PRIZM #YASHTechnologies

Meet us at Snowflake Summit 2026. Booth 2739. June 1 to 4, Moscone Center. Your Snowflake estate scales automatically. Your data trust doesn't. PRIZM makes Data Quality, Observability, and Context work as one self-driving system on Snowflake. We're showing it live at the booth. No slides. Just the product. Schedule the meeting today - https://lnkd.in/dHGxDADT #SnowflakeSummit2026 #DataObservability #Snowflake #PRIZM

We’re excited to announce that DQLabs is bringing data quality signals directly into ServiceNow Data Catalog! With quality, freshness, and anomaly signals visible on cataloged assets, organizations can understand data health earlier and work with confidence. - Stewards can certify trusted data products faster - Analysts and business teams can evaluate fitness for use quickler - Governance leaders can report on trust using shared business context By bringing trust signals into the catalog experience, teams get the context they need without jumping across systems. Announced at ServiceNow Knowledge 2026, this new integration builds on DQLabs’ established ServiceNow ITSM integration. Read more here: https://lnkd.in/gzbD3HPC #DataQuality #DataObservability #DataGovernance #ServiceNow #ServiceNowKnowledge2026 #DQLabs #DataTrust

Enterprise AI initiatives are accelerating. Most data foundations are not keeping up. The gap is structural. #Observability, #Quality, and #Context live in separate tools. Alert triage is manual. Remediation depends on whoever happens to be on-call. The data your AI models consume is only as trustworthy as the last person who checked it. Check out our on-demand session, why self-driving data platforms require more than automation overlays on legacy architectures, and how #PRIZM introduces an AI-native control plane that understands context, evaluates trust, prioritizes risk, and resolves issues before they reach analytics or AI systems. The session covers why legacy data foundations fail at AI-scale demands, the role of self-driving control planes in enterprise data trust, and how PRIZM enables AI-ready data by design, not by manual intervention. Worth 30 minutes if you are a CDO, data architect, or engineering lead evaluating how to close the gap between your AI ambitions and your data reality https://lnkd.in/dZ4S3UFy #AIReadyData #DataObservability #DataQuality #PRIZM #AgenticAI

Snowflake is not a database. It is a cloud data platform with elastic compute, credit-based pricing, and an expanding ecosystem of dbt, Snowpipe, Tasks, and Streams. So why do most observability tools still monitor it like it is Postgres? #PRIZM was built from the metadata up to understand how Snowflake actually works. Criticality-aware profiling means your CFO's revenue table gets deep checks. The forgotten staging table from 2019 gets nothing. Your credit bill stays predictable even as your catalog grows into tens of thousands of assets. We broke down the 7 layers you actually need to observe and the 10 capabilities to demand before you sign with any vendor. https://lnkd.in/djYSuUpj #DataObservability #Snowflake #DataQuality #AIReadyData #DataEngineering #PRIZM

Gartner Data & Analytics Summit 2026, London. We'll be at Booth 316. Catch Venkatesh Perumal Field CTO, DQLabs on May 11 at 5:10 PM as he walks through how PRIZM the industry’s first AI-native platform where Data Observability, Data Quality, and Context work together as one system. Then swing by Booth 316 and see it in action against your actual use case. https://lnkd.in/dzDwzJhE #GartnerDA #DataAnalytics #DataQuality #DataObservability #DQLabs #PRIZM hashtag#London

Databricks has seven layers to observe: compute, ingestion, storage, transformation, governance, ML, and consumption. Miss one and you own the next incident. We mapped all seven and the ten capabilities your tool needs to cover them. Check out how PRIZM approaches data observability for Databricks. https://lnkd.in/d4vs5mpC #Databricks #Lakehouse #PRIZM #DQLabs