DQLabs Named
A Visionary
in the 2025 Gartner® Magic Quadrant™ For Augmented Data Quality Solutions
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End-to-End
Data Observability for Reliable Data
Ensure data reliability with proactive monitoring, automated anomaly detection, and comprehensive visibility across data, pipelines, and reports.
Common Data Observability Challenges
Monitor Data Quality
Continuous Monitoring for Accurate, Trusted Data
DQLabs continuously monitors data health, detecting and resolving inconsistencies instantly to ensure accurate and reliable insights for decision-making.
Trace Data Lineage
Complete Transparency Across Pipelines
Get full data lineage visibility with DQLabs, enabling fast issue resolution, reduced downtime, and maintained data integrity from source to destination.
Proactive Alerting and Notifications
Faster Fixes, Less Downtime
DQLabs uses advanced AI/ML techniques to identify outliers in real time, preventing analytical errors and enabling proactive issue resolution to reduce downtime.
Data Content Observability
- Out-of-the-box checks for Schema, Volume, Freshness, and Uniqueness to ensure data reliability.
- AI/ML-driven anomaly detection and resolution of unknown anomalies.
- Automated alert prioritization for effective issue resolution and reduced alert fatigue.
Pipeline Observability
- Granular and component-level monitoring of pipelines (Runs, Jobs, Tasks, Tests) with component-specific charts and alerts linked to them.
- Automated lineage to quickly trace and fix broken pipelines by identifying root causes of data issues.
- Comprehensive pipeline management with support for dbt, Azure ADF, Airflow, Fivetran, and Talend.
Usage Observability
- Centralized visibility into query behavior across all configured cloud data warehouses and RDBMS connections.
- Granular query insights with detailed execution statistics (total queries, average, max, and min execution times) for each asset.
- Enhanced cost management and query optimization by identifying and addressing long-running or inefficient queries, enabling proactive compute cost control.
Reports Observability
- Centralized visibility into Power BI and Tableau reports to track data health and ensure report reliability.
- Table and column-level lineage to trace upstream data issues, accelerating root cause identification and resolution.
- Integration with collaboration tools like Slack or Jira for efficient communication and issue resolution across teams working on BI reports.
Frequently Asked Questions
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Do you monitor data on-premises?
Yes, DQLabs is an ideal tool for monitoring and observability for multi-cloud or hybrid-cloud workloads. We support both on-premises and cloud environments.
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How does DQLabs help with alert fatigue?
DQLabs’ AI/ML-driven anomaly detection categorizes all data quality anomalies as high, medium, or low priority, based on the deviation from historical data. This helps users focus on high-priority alerts for an effective issue-resolution process.
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How does DQLabs' data observability platform integrate with existing data tools and workflows?
DQLabs provides out-of-the-box connectors for major data warehouses, data lakes & lakehouses, ETL/ELT tools, catalogs and BI tools. Users can embed data quality checks in their data pipelines with our integrations with tools like Airflow and dbt. Our bi-directional integration with leading data catalogs like Collibra and Alation allows users to easily access data quality metrics of their datasets. To read more about our connectivity with other tools please visit our integration page.
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How does DQLabs go beyond data observability?
DQLabs provides out-of-the-box table-level observability checks to detect volume, schema, freshness, and uniqueness related issues. DQLabs also provides attribute-level data observability with its AI/ML-driven anomaly detection. AI-powered anomaly detection automatically understands the trends and patterns of data and uses these benchmarks to generate alerts for data anomalies. DQLabs also provides a comprehensive lineage to show the complete data journey from upstream to downstream data sources which helps users in root cause analysis.