Relying on manual DQ checks and validations leads to inefficiencies, increased errors, and delays in identifying and addressing data quality issues.
Alert Fatigue
Excessive low-priority alerts overwhelm teams, making it difficult to prioritize critical issues and causing delays in resolving data quality problems effectively.
Undetected Data Anomalies
Unknown data quality issues remain hidden, leading to undetected anomalies and downstream impacts that could affect business operations and analytics initiatives.
Pipeline Failures and Unpredictability
Schema changes, unexpected values, or pipeline delays disrupt workflows, introduce errors, increase data downtime and make it challenging to maintain reliable data flows across systems.
Delayed Detection of Data Issues
Without real-time monitoring and automated anomaly detection, unexpected values, nulls, and schema changes often go unnoticed, impacting downstream systems and applications.
Overcome your Quality Challenges with DQLabs
GenAI-driven Data Quality
Conversational Data Quality for All Personas: Focused on delivering a seamless experience for both technical and non-technical users.
Simplified user queries: Users can ask questions, request data profiles, explore data quality metrics, and execute data quality rules.
Enhanced usability: Simplifies the usability of the platform, reducing the need for technical expertise to perform data quality tasks.
Data Quality Automation and Monitoring
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.
Deep Data profiling: Out-of-box measures to analyze the data to profile at basic and advanced levels depending on specific use cases.
Performance Metrics: Real time data quality monitoring for unexpected values, nulls, schema changes, data volumes, types, value frequencies, and formats.
Anomaly Detection and Alerts prioritization
AI/ML-driven anomaly detection to take care of unknown data quality issues.
AI/ML-driven alert prioritization, based on the deviation from the historical trends, for effective issue resolution and reduced alert fatigue.
Integration with popular issue management tools and communication channels like Jira, Slack, and BigPanda for seamless issue management and resolution.
Data Lineage and Governance
Visual map of your data journey from upstream sources to downstream systems and applications to accelerate the issue identification and resolution process.
Granular controls on asset ownership, and data usage with granular role-based access controls.
Bi-directional integration with leading data catalog tools for enhanced data cataloging and data quality automation.
Platform Flexibility and Usability
Flexible deployment options tailored to your needs: Traditional on-premises, Data Quality PaaS, Data Quality SaaS, and public or private cloud infrastructure.
Connectivity: Seamless integration with a wide range of leading data warehouses, data lakes, lakehouses, RDBMS, ETL tools, data transformation tools, catalogs, and issue and communication management tools.
Tailored for a comprehensive audience, including Data Leaders (CDO/CDAOs), Business Stakeholders, Data Stewards, Data Scientists, Data Analysts, Citizen Users, Data Engineers, and DataOps professionals.
What Our Clients Are Saying
City of Spokane Enhances Public Safety with DQLabs
“DQLabs helped us deliver a consistent source of high-quality data to address high-risk populations’ concerns and improve public safety and community planning.”
Tacoma Public Utilities Enhances Data Discovery with DQLabs
8x
Improvement in data discovery and issue resolution
“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.
