The Modern Data Quality Platform

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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

Improved data reliability and data availability SLAs

Improved downstream quality of data

Automation across all three levels of data quality checks

Elimination of manual rules via automation

Remediation-centric data collaboration

Personalized Data Quality feeds and Dashboards

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.

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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.

METADATA

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.

CONTENT | CONTEXT

Features

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 across warehouses, data lakes, orchestrations, business intelligence tools, and channels.

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.