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- DQLabs Platform
One unified platform for data leaders, engineers, and analysts—offering observability, quality, discovery, and remediation.
- Agentic AI Data Management
An autonomous, Agentic AI driven capabilities to continuously improve management of data issues.
- DQLabs Capabilities
Automated data quality, anomaly detection, semantics-driven discovery, and issue resolution for trusted and reliable data.
- Data Observability
Monitor data, pipelines, and usage—detect anomalies, ensure reliability, and optimize the health of your data systems.
- Data Quality
Automate data quality with no-code checks, anomaly detection, lineage, and governance for trusted, accurate, and reliable data.
- Data Discovery
Discover data with semantics-driven categorization, advanced search, and catalog integration for faster, actionable insights.
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Ensure Efficient Data Quality Management for Azure AD

Overview

Azure Active Directory (Azure AD) is Microsoft’s cloud-based identity and access management service that allows organizations to manage users, devices, and apps securely. While Azure AD offers robust identity protection and access control, it doesn't provide built-in data quality monitoring or observability for the data linked to user identities, roles, or permissions. Without data quality checks, businesses risk using inaccurate user data, potentially compromising security, compliance, and decision-making.

DQLabs enhances Azure AD by integrating end-to-end data quality and observability, ensuring the integrity of identity-related data and empowering businesses to make secure, reliable decisions.

DQLabs integrates seamlessly with Azure AD, providing automated data validation, anomaly detection, and comprehensive observability for identity-related data. By combining Azure AD’s powerful identity management with DQLabs’ real-time monitoring, businesses can ensure the reliability and security of user, role, and permissions data. DQLabs tracks changes in access control, detects anomalies, and validates data for accuracy and completeness, ensuring compliance, reducing security risks, and improving decision-making.

With DQLabs, organizations can maintain governance over their identity data, minimize errors, and prevent access control issues caused by bad data.

Data Quality and Observability for
Azure Active Directory

Identity Data Validation

Ensure the accuracy and completeness of user identities, roles, and access permissions by validating data in Azure AD. DQLabs checks for inconsistencies, incomplete records, or errors in identity data, ensuring that only valid information is used across systems and applications.

Role and Permission Consistency Monitoring

Continuously monitor changes in user roles and permissions in Azure AD to ensure that access control is always up to date and consistent. DQLabs alerts organizations when unexpected changes occur, preventing unauthorized access or role mismatches.

Anomaly Detection in User Access Patterns

Detect irregular or suspicious patterns in user activity and access attempts. DQLabs uses AI-driven anomaly detection to flag unusual behavior such as unauthorized access or unexpected role changes, ensuring that security protocols are followed at all times.

Data Lineage and Compliance Tracking

Track the full lifecycle of identity and access data across systems to ensure compliance with regulatory standards. DQLabs helps organizations maintain an auditable trail of identity-related data, aiding in security audits and ensuring adherence to security policies and governance practices.

Access Control Integrity

Verify the completeness and accuracy of user access control information before granting permissions to sensitive data. DQLabs ensures that user roles and permissions are based on trustworthy, real-time data, avoiding access control errors and security breaches.

Seamlessly Integrate with your
Modern Data Stack

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DQLabs Named A Visionary

Ensure Efficient Data Quality Management for Azure AD

Overview

Data Quality and Observability for Azure Active Directory