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Enhancing Financial Data Quality The JMMB Journey
Webinar|25th February 2025| 11 AM EST
Webinar
25th February 2025
11 AM EST
Register NowData Quality
for Every Persona,
Every Need
A unique platform designed to serve the diverse needs of data leaders, engineers, analysts, and business users.
A Unified Platform for All Data User Personas!
One Platform, Tailored Solutions: Powered by OMDR
Observe
Detect unknown reliability issues across your data ecosystem to resolve any data issues faster than ever before for both data in rest and motion.
Measure
No code, automated business quality-focused checks for known issues across domains to ensure data is fit for purpose.
Discover
Auto-discover rules and leverage standardized checks on business terms for improved governance and stewardship.
Remediate
Augmented, plus GenAI enabled remediation combined with the power of semantics.
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.
One Platform, Tailored Solutions: Powered by OMDR
Observe
- Data Observability: Pre-built checks for data validity, completeness, freshness, and uniqueness to ensure data reliability.
- Pipeline Observability: Ensure seamless monitoring and visibility into data pipelines, enabling proactive issue detection and reliable data delivery.
- Data Usage: Gain deep insights into query behavior to optimize performance and control costs across your data infrastructure.
Measure
- Data Profiling: Out-of-the-box measures for basic and advanced data profiling to assess data structure and identify inconsistencies, ensuring data validity and completeness.
- Out-of-the-box DQ Checks: Ensure data trustworthiness across all dimensions - accuracy, completeness, uniqueness, validity, and timeliness.
- Customizable DQ Checks: Platform-level and asset-level custom no-code data quality checks, with flexible query mechanisms and conditional logic, ensuring comprehensive data quality coverage.
Discover
- Self-Service Data Discovery: A user-friendly platform that provides visibility of business terms and quality metrics across your entire data ecosystem.
- Semantic Layer: Ability to define semantic terms, tags, and applications 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.
Remediate
- AI/ML-Powered Anomaly Detection: Continuously monitor data flows and proactively address data quality issues before they disrupt critical processes.
- Issue Management: Integration with Jira, Slack, and other workflow management tools to streamline the issue resolution process.
- Data Lineage: Comprehensive table and column-level lineage, allowing users to trace upstream data issues, significantly reducing the time to identify root causes.
Seamlessly Integrate with Your
Modern Data Stack
Trusted by
Enterprises Globally
Frequently Asked Questions
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Are DQLabs’ anomaly detection capabilities equipped with customizable thresholds and rules?
Yes, DQLabs’ anomaly detection capability is not limited to the AI & ML-based default configuration. DQLabs allows users to select the manual threshold as per their specific data quality requirements.
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What integration options does DQLabs offer for connecting with other data sources and tools?
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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If I use the DQLabs platform, will my data remain on-premises?
Yes, that's right. DQLabs leverages your metadata for data quality operations.
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Does DQLabs support both on-premises and cloud data environments?
Yes, DQLabs is an ideal tool for multi-cloud or hybrid-cloud workloads. We support both on-premises and cloud environments.
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Can I customize data quality rules in the DQLabs platform?
Yes, in addition to its out-of-the-box rules, DQLabs provides customizable no-code DQ checks. Users can configure these rules at the platform level and at asset level.
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Does DQLabs provide Role-Based Access Control (RBAC)?
Yes, DQLabs provides role-based access control (RBAC), allowing admins to define feature access for different roles. Additionally, admins can set granular permissions to specify what actions each role can perform within those features.