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Overview
BigID is a data intelligence platform for discovery, privacy, and security across data stores. However, enterprise rollout can be complex. Still, accurate classification, automated remediation, and governance workflows help reduce risk and align operations with regulatory requirements.
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Starting Price
Custom
BigID Specifications
Data Encryption
Threat Intelligence
Multi-Factor Authentication
Security Audits And Reporting
What Is BigID?
BigID is designed for enterprises that need visibility into sensitive data across structured and unstructured sources. It discovers and classifies regulated information, then automates actions such as redaction and deletion. Privacy workflows for regulations like GDPR and CCPA streamline requests, while security posture tools guide controls across hybrid environments.
BigID Pricing
BigID Integrations
Who Is BigID For?
BigID is ideal for a wide range of industries and sectors, including:
- Financial services
- Healthcare and life sciences
- Insurance
- Technology
- Retail and e-commerce
- Public sector
Is BigID Right For You?
BigID fits organizations with large, diverse data estates seeking consistent discovery and governance. Its AI-driven classification and privacy workflows can reduce manual effort while improving audit readiness. If centralizing risk insight across clouds and on-premises is a goal, the platform merits consideration.
Still doubtful if BigID is the right fit for you? Connect with our customer support staff at (661) 384-7070 for further guidance.
BigID Features
AI models scan databases, file shares, object stores, and applications to locate personal and regulated data. Centralized inventories help teams understand exposure and enforce policies where data resides, which is essential for audits and incident containment.
Detection findings can trigger actions like redaction, deletion, or access revocation. Automating these steps reduces response time and human error, which lowers risk and helps administrators maintain consistent controls across busy environments.
Risk scoring and policy checks surface weak controls across repositories. Administrators can prioritize improvements and monitor progress, which aligns stakeholders on a shared view of data risks and the steps required to address them.
Prebuilt workflows support data mapping, subject access requests, and consent management. Coordinating these processes in one place reduces manual handoffs and demonstrates compliance with regulatory timelines during audits or supervisory reviews.
Governance for training and inference datasets helps teams document sources, limit sensitive attributes, and meet emerging AI requirements. This reduces uncertainty when models rely on complex data pipelines and supports responsible AI initiatives.
