
Sensitive Data Discovery, Data Masking. Access Controls.

Mage Static Data Masking is a comprehensive solution designed to protect sensitive data by creating permanently masked, obfuscated, or anonymized copies of production data. This approach supports application development, data analytics, and testing while safeguarding sensitive information such as Personally Identifiable Information , Protected Health Information , and Non-Public Information from unauthorized access. By ensuring compliance with privacy regulations like GDPR, CCPA, and HIPAA, Mage Static Data Masking minimizes risks in less secure environments without compromising data usability. Key Features and Functionality: - Diverse Anonymization Techniques: Offers over 80 anonymization methods, including masking, encryption, and tokenization, allowing organizations to choose the most suitable technique for their needs. - Data Integrity Maintenance: Ensures referential integrity across applications and data stores, preserving data usability for development and analytics purposes. - Compliance and Customization: Provides pre-configured policies for regulations such as GDPR, CCPA, and HIPAA, with the flexibility to customize policies to meet unique data protection requirements. - Support for Various Data Formats: Handles structured , semi-structured , and unstructured data formats, ensuring broad applicability. - Advanced Capabilities: Features automated data discovery and classification, privacy compliance functionalities like Right to Erasure , and lifecycle management for sensitive data. Primary Value and Problem Solved: Mage Static Data Masking addresses the critical need for securing sensitive data in non-production environments. By anonymizing or encrypting data, it protects against unauthorized access, ensuring compliance with global privacy regulations. The solution maintains data integrity and usability, allowing organizations to conduct development, testing, and analytics without exposing sensitive information. Its versatility across various data formats and advanced capabilities like automated data discovery make it a robust tool for comprehensive data protection strategies.

Enterprise sensitive data masking is complicated. It's not just the diversity of data sources, or differing user requirements, or the need to maintain data consistency; it's also performance requirements, effective multi-stakeholder participation, and agility in deployment that make masking so complex.

Mage Sensitive Data Retirement is a comprehensive solution designed to help organizations manage and protect sensitive data throughout its lifecycle. By automating the identification, monitoring, and secure retirement of inactive sensitive data, it ensures compliance with global privacy regulations and minimizes the risk of data breaches. This platform enables businesses to maintain data integrity while effectively responding to data subject rights requests, such as the Right to Erasure and Right to Access. Key Features and Functionality: - Data Flow Mapping: Accurately maps data flow within the enterprise, providing clear insights into data proliferation and aiding in comprehensive data governance. - Automated Subject Rights Requests Handling: Facilitates automated and thorough responses to data subject rights requests, ensuring timely compliance with regulations. - Inactive Data Identification: Configures rules to identify inactive sensitive data based on organizational policies, enabling efficient data management. - Secure Data De-identification: Safely de-identifies operational data while preserving the transactional integrity of data stores, maintaining data usability. - Tokenization and Deletion: Implements secure tokenization or deletion of sensitive data, reducing exposure risks and ensuring compliance with data minimization principles. Primary Value and Problem Solved: Mage Sensitive Data Retirement addresses the critical challenge of managing sensitive data that is no longer actively used but still poses security and compliance risks. By automating the retirement and de-identification of such data, the solution reduces the potential for unauthorized access and data breaches. It also streamlines compliance with privacy regulations by efficiently handling data subject rights requests, thereby enhancing overall data governance and security posture.

Mage Database Activity Monitoring is a comprehensive solution designed to enhance the security of sensitive data within organizational databases. It empowers data security professionals to monitor and analyze access to critical information, ensuring compliance with global privacy regulations and maintaining an audit-ready state. By providing near-real-time reporting capabilities, Mage enables organizations to detect and respond to unauthorized activities promptly. Key Features and Functionality: - Anomaly Detection: Establishes baseline activity patterns for users and applications, identifying deviations that may indicate security threats. - User and Application Monitoring: Configures and logs activities of authorized and unauthorized users and applications, offering detailed insights into database interactions. - Near-Real-Time Reporting: Delivers timely reports on database activities, facilitating swift responses to potential security incidents. - Compliance Demonstration: Maintains detailed records of all database activities, aiding in adherence to privacy regulations and simplifying audit processes. Primary Value and Problem Solved: Mage Database Activity Monitoring addresses the critical need for organizations to secure sensitive data against unauthorized access and potential breaches. By offering continuous monitoring and detailed reporting, it enables businesses to detect anomalies, ensure compliance with privacy laws, and maintain the integrity of their data environments. This proactive approach minimizes the risk of data breaches and supports organizations in safeguarding their most valuable information assets.

iDiscover, found volumes of data in these places when rudimentary discovery had failed to do so. Other solutions can find some of the information in some of the places some of the time. MENTIS can find all of the places all the time.



Mage, accessible at [magedata.ai](https://magedata.ai/), offers an open-source data pipeline tool designed to facilitate the ingestion, transformation, and orchestration of data. Mage focuses on making it easier for data engineers and analysts to build, manage, and maintain data workflows with a streamlined interface and robust features. By supporting various data sources and enabling code-first as well as no-code options, Mage aims to enhance productivity and flexibility in handling complex data operations.