As organizations accelerate their adoption of generative AI (GenAI), one of the most critical and often overlooked challenges is managing and cataloging données non structurées. From emails and documents to cloud storage repositories and collaboration tools, unstructured data makes up a significant portion of an enterprise’s digital footprint. Without a robust strategy to handle this data, organizations face security risks, compliance violations, and inefficiencies in AI-driven innovation.
The Role of DSPM in Managing Data Risk
Gestion de la sécurité des données (DSPM) has emerged as a key solution for discovering and protecting sensitive data across cloud and SaaS environments. DSPM provides organizations with visibility into high-risk data assets—whether they stem from regulatory obligations (e.g., GDPR, HIPAA) or security vulnerabilities such as over-permissioned or exposed data.
However, traditional DSPM solutions have primarily focused on structured data, leaving gaps in unstructured data governance. This is where an evolved approach—moving from DSPM to a comprehensive Data Security Platform (DSP)—becomes critical.
The BigID Approach: From DSPM to DSP
BigID stands out in the DSPM market by offering a broader, more integrated Data Security Platform. This approach ensures organizations can manage both structured and unstructured data with a unified solution. Here’s how BigID addresses key challenges:
1. Comprehensive Data Discovery
Undiscovered data is unprotected data. BigID supports a vast array of sources de données, spanning SaaS platforms (e.g., Salesforce, ServiceNow), cloud environments (e.g., Flocon de neige, AWS, L'azur), and collaboration tools (e.g., Slack, Google Drive, Microsoft 365). With advanced AI-powered classification, organizations can:
- Identify sensitive unstructured data across diverse repositories.
- Automatically categorize documents, emails, and files.
- Detect duplicate, orphaned, and stale data that adds unnecessary risk.
2. Advanced AI-Powered Classification
Unlike traditional DSPMs that rely on predefined regular expressions, BigID offers:
- AI-driven classification to adapt to unique business needs.
- Exact data matching for highly sensitive information.
- Natural language processing (NLP) to categorize unstructured data.
- Customizable classifiers to accommodate evolving regulatory and business requirements.
3. Risk Posture Analysis for Unstructured Data
Organizations need visibility into the risks associated with unstructured data. BigID provides:
- Insights into data sensitivity and security posture.
- Automated mapping of data to compliance frameworks.
- Identification of over-permissioned and over-shared data.
- Detection of shadow data and misconfigured access controls.
4. Actionable Remediation
Beyond identifying data risks, BigID enables remediation through a range of automated actions:
- Delegated remediation workflows to ensure data owners address security issues.
- Gouvernance de l'accès aux données (DAG) to manage permissions and access controls.
- Retention management to reduce redundant, obsolete, and trivial (ROT) data.
- Integration with SIEM, SOAR, and ticketing systems for streamlined security operations.
Integrating Privacy and Security in GenAI Programs
Data privacy and security are no longer separate concerns—especially as organizations leverage GenAI models trained on vast datasets. Without a proper strategy, AI models can inadvertently ingest sensitive unstructured data, leading to:
- Compliance violations (e.g., data retention laws, réglementation sur la confidentialité).
- Intellectual property risks from unauthorized data access.
- Data integrity challenges affecting AI outputs.
BigID’s integrated privacy and security suite ensures:
- Automated data subject rights (DSR) fulfillment under GDPR/CCPA.
- Identity-aware data discovery for AI model governance.
- Policy-driven labeling and tagging for sensitive content.
Future-Proofing Data Security with a Unified Platform
As organizations scale their GenAI initiatives, the need for a future-proof data security platform becomes paramount. BigID’s DSP approach allows companies to:
- Consolidate security and privacy management across structured and unstructured data.
- Extend capabilities with modular apps tailored to AI-driven use cases.
- Maintain compliance with evolving regulatory landscapes.
Conclusion
Unstructured data represents both a massive opportunity and a significant risk in the era of GenAI. Organizations must adopt a comprehensive approach to discovery, classification, risk analysis, and remediation to harness the full potential of AI while ensuring compliance and security. By transitioning from DSPM to a robust Data Security Platform, enterprises can confidently scale their AI programs with a foundation built on trust, governance, and intelligent automation.
Secure, classify, and manage your unstructured data—because AI is only as good as the data it’s trained on.
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