The Forrester Wave?: Data Security Platforms, Q1 2023 reportRead the report
Address data privacy and governance with 好色先生TV? Core Data Discovery & Risk Insights (好色先生TV? Voltage Fusion Platform), a cloud-first data security platform. Connect data discovery, classification, and insight to data security, usage monitoring, and lifecycle management.
Scan any repository or service to classify data according to type, risk sensitivity, and potential financial impact, to prioritize risk reduction.
Replace manual remediation with automated, privacy-aligned data protection technologies that improve compliance and promote strong data ethics and business growth.
Use data discovery to power data security, privacy, and governance use cases while supporting corporate financial, operational, and ESG or sustainability goals.
Protect customer data while retaining its business value for safe use in data science and secure data sharing outside your enterprise.
Detect regulated information (PII, PCI, PHI) across unstructured and structured data, including rich media analysis of image, audio, and video files.
Confidently analyze and classify sensitive data in compliance with global industry, financial, and data privacy laws.
Go beyond simple risk scoring by connecting data discovery and classification to the potential monetary and business impact of sensitive data exposure or non-compliance.
Connects to virtually any repository, off and in the cloud, to create and configure data ingestion, identification, and management.
Deidentifies data to render it useless to attackers while maintaining its usability and referential integrity for data processes, applications, and services.
Guarantees only authorized users with appropriate roles can access data when needed and enables change notifications, lifecycle management, security lockdown, and security fencing.
Actively monitors all database activities in real time, generates alerts for any policy violations, identifies passive databases, and increases observability on how and where data is used.
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