Compare Mage Sensitive Data Discovery vs. SISA Radar in 2025

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Description

Mage Sensitive Data Discovery module can help you uncover hidden data locations in your company. You can find data hidden in any type of data store, whether it is structured, unstructured or Big Data. Natural Language Processing and Artificial Intelligence can be used to find data in the most difficult of places. A patented approach to data discovery ensures efficient identification of sensitive data and minimal false positives. You can add data classifications to your existing 70+ data classifications that cover all popular PII/PHI data. A simplified discovery process allows you to schedule sample, full, and even incremental scans.

Description

Assist organizations in enhancing their data protection strategies through the utilization of data discovery, file analysis, and classification techniques. Safeguard your entire data environment with SISA Radar's capabilities in data discovery and classification. Effectively arrange and categorize sensitive data according to its importance and organizational requirements. Acquire contextual insights that facilitate improved management of sensitive information. Achieve comprehensive visibility into various forms of sensitive data, including structured, semi-structured, and unstructured types. Ensure the safeguarding of data against unauthorized access while adhering to compliance standards such as PCI DSS, GDPR, CCPA, POPIA, PDPA, APRA, and other privacy regulations. Develop and personalize your own data classification framework to suit specific needs. Adopt a scalable and resilient strategy for advanced data security in the future. Utilize a singular platform designed to uncover, identify, and contextualize sensitive information efficiently. With a proprietary data discovery algorithm, experience quicker detection times and a significant reduction in false positives, ultimately enhancing your overall data protection efforts. This comprehensive approach will ensure that your organization remains resilient in the face of evolving data security challenges.