The Modern Data Quality Platform

Improve your data relevance

DQLabs is a Modern Data Quality-centric Observability platform for enterprises to deliver data relevance.

The DQLabs platform is an out-of-the-box platform solution that provides instant data quality alerts, but also measures, and metrics for all personas to collaborate and see Data Quality issues in their own ways to improve business outcomes.

  • No-code observability engine
  • Elimination of manual rules via automation
  • Improved data reliability and data availability SLAs
  • Remediation-centric data collaboration
  • Improved downstream quality of data
  • Personalized Data Quality feeds and Dashboards
  • Automation across all three levels of data quality checks

Data minds and Business minds see data in different ways even when working on the same data for the same business outcomes. You need a platform that promotes Decentralized Data ownership culture to improve data relevance and data collaboration.

Decentralized Data Ownership

by providing a data quality collaborative workspace to improve data to business relevance across all personas.

Data Minds

Builds maintains Data infrastructure, data products, use analysis and algorithms to deliver a single source of truth downstream to all end-user tools for democratized data.


Business Minds

Collects, processes, and uses data to make business analysis on large dataset better, faster decisions and result in direct business outcome or value as strategies evolve and refine.



DQLabs platform features span across both Data minds ( personas such as Data Engineers, Data Scientists, and Data Analyst) and Business minds (Data Stewards, SMEs, and Data Leaders) who view the same data but relate to and measure data quality in different ways or relevant to their roles and responsibilities. This enables a DQ-focused collaborative platform that results in a direct business outcome irrespective of the size of the organization or data maturity cycle.

Smart Connectors
Connect to unlimited data sources in any form, shape, location
Semantic Discovery
Automatically discovers business terms using semantic identification and classification algorithms.
Observe Data Drift
Continuous monitoring of data drift using both univariate and multivariate anomaly detection algorithms.
Measure Data Quality
Look inside the data content across subjective and objective data quality dimensions.
Remediate Data Quality Issues
Using semantic powered context and detailed information, remediate data quality issues with 100% confidence.
Business Scorecards and Insights
Outcome-focused measurement from top to bottom using KPI metrics, business measures, and data availability alerts.

With these features, you can now measure business strategies and their relevant data from top to bottom across domains and functional owners promoting a decentralized data ownership culture and improving data relevance. The platform can scale depending on your data maturity cycle irrespective of whether you are just starting out in the process of Data Quality or already working with an ecosystem full of data governance, catalog, and management platforms.

Best Practices

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DQLabs in Action: Data Collaboration in the Modern Data Stack

Demand for data drives collaboration. For many data leaders, the mandate is clear: use data to deliver business value. And, with new use cases and data-intensive analytic methods, demand for data has exploded. Innovative data leaders have begun to break down silos within their organizations, and realize that just having a modern data stack is not enough.

Join us on this webinar to learn how the DQLabs platform is the Modern Data Quality Platform eliminates critical data silos by centralizing Data Observability, Data Quality, and Data Discovery into a single, agile AI-driven platform.


12:00 pm: Welcome & Introductions

12:05: pm: Industry Insights: Data Collaboration in the Modern Data Stack

12:15 pm: DQLabs in Action: Top-Down Data Health with the DQLabs Platform 

12:30 pm: Questions & Answers

12:45 pm: Close

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