Is Your Organization Struggling with Any of These Data Issues?
Data Integrity
Frequent issues with data anomalies, schema changes, and inconsistencies can lead to unreliable insights and decision-making delays.
Pipelines Unpredictability
Bottlenecks, delays, and undetected errors in data pipelines create roadblocks, slow down workflows, and complicate troubleshooting.
Limited Visibility into Data Usage
Lack of insight into data access and usage patterns increases risks of non-compliance, inefficient resource allocation, and potential misuse.
Alert Fatigue
Excessive notifications and low-priority alerts make it difficult to stay focused on critical issues, leading to slower response times and missed data issues.
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.
Overcome Your Data Issues with DQLabs' Data Observability Solutions
Data Content Observability
Maintain Data Integrity with Near Real-Time Monitoring and Automated Insights
Continuous Data Quality Monitoring: Track data health to detect anomalies, missing values, and data integrity issues.
Schema Evolution Tracking: Automatically monitor schema changes to ensure compatibility and prevent unexpected downstream disruptions.
Rule-based & ML-driven Validation: Apply both rules and machine learning based DQ checks to enforce data standards and catch quality issues proactively.
Data Pipeline Observability
Full Visibility and Control Over Data Pipelines from End-to-End
End-to-End Data Lineage: Trace data flow across pipelines, making it easy to diagnose bottlenecks and pinpoint errors.
Real-Time Pipeline Monitoring: Get instant alerts on data delays, failures, or unexpected transformations within pipelines.
Impact Analysis: Assess how pipeline issues affect downstream systems, helping to prioritize fixes and minimize disruptions.
Performance Metrics: Monitor throughput, latency, and resource usage to optimize pipeline performance and reduce processing time.
Users, Usage, and Utilization
Track Data Access, Usage Patterns, and Utilization for Improved Governance and Efficiency
User Access Monitoring: Track user interactions with data to identify usage patterns and ensure compliance.
Data Usage Analytics: Understand how data assets are consumed across the organization to inform access and retention policies.
Utilization Insights: Gauge the effectiveness of data resources, identifying underused datasets or overutilized pipelines.
User Behavior Analysis: Detect unusual usage patterns that could indicate potential data misuse or compliance risks.
Proactive Alerting and Notifications
Stay Ahead of Data Issues with Custom Alerts and Instant Notifications
Customizable Alert Thresholds: Set threshold alerts for data anomalies, schema changes, and pipeline issues.
Real-Time Notifications: Receive instant alerts across channels (email, Slack, Teams) for immediate response.
Priority-Based Alerts: Classify alerts by impact level to focus on the most critical issues first.
The DQLabs platform harnesses the combined power of Data Observability, Data Quality, and Data Discovery to enable data producers, consumers, and leaders to turn data into action faster, easier, and more collaboratively.
Detect unknown reliability issues across your data ecosystem to resolve any data issues faster than ever before for both data at rest and in motion.
Data Observability
Monitor and resolve your data issues before they affect your downstream operations.
Data content: Track data accuracy, completeness, and integrity. Detect anomalies, errors, and schema changes automatically.
Data flow and pipeline: Monitor data pipelines, resolve bottlenecks, and catch broken pipelines or failed jobs in real time.
User, usage and utilization: Identify data usage patterns, track user access, and spot unusual activity for optimized security and performance.
No code, automated business quality-focused checks for known issues across domains to ensure data is fit for purpose.
Data Quality
Ensure data accuracy and trust
50+ OOB DQ checks: Ensure data accuracy and trustworthiness with DQLabs out of the box DQ checks for all dimensions - Accuracy, Completeness, Consistency, Uniqueness, Validity, and Timeliness.
Customizable DQ checks: Customize data quality checks with flexible query mechanisms and conditional logic for specific use case requirements.
Data profiling: Out-of-box measures to analyze the data to profile at basic and advanced levels depending on one's use case.
Auto-discover rules and leverage standardized checks on business terms for improved governance and stewardship.
Data Discovery
Simplify the way you find and understand your data
Self-service data discovery: A user-friendly platform that provides End-to-end visibility of business terms and quality metrics across your entire data ecosystem.
Semantic layer: Ability to define semantic terms, tags, applications, dimensions, and fields for effective data categorization.
Catalog and governance integration: Bi-directional integration with leading catalog and governance tools for enhanced data cataloging, automated data quality, and Increased trust in data.
Augmented, plus GEN AI enabled remediation combined with the power of semantics.
Anomaly Detection and Alert Prioritization
Timely issue detection with smart alert prioritization
AI/ML powered anomaly detection: AI/ML-powered anomaly detection to continuously monitor data flows, comparing current values against historical benchmarks.
Alerts prioritization: DQLabs Automatically prioritize alerts by deviation severity—high, medium, or low—so you can focus on the most critical data issues first.
Issue management: Integrate with Jira, Slack, and more to streamline issue resolution, enhance collaboration, and drive faster decisions.
What Our Clients Are Saying
Leading Waste Management Company Achieves 10X Improvement in DQ
“By using DQLabs, We automated the end-to-end business process and were able to continuously monitor the critical data elements with better productivity..”
Seamlessly integrate with your Modern Data Stack
Recognitions & Partnerships
Let our experts show you the combined power of Data Observability, Data Quality and Data Discovery.
