Privacy Management With Intelligent Data Classification for AI Models

In today’s age of AI, organizations leverage vast amounts of data to fuel these powerful models. But a hidden challenge lurks: a significant portion of this data remains unstructured and unseen, creating a blind spot for privacy. This “dark data” can harbor sensitive information – a goldmine for those looking to exploit it. Zubin, Data Dynamics’ AI-powered self-service data management software, empowers you to navigate the tightrope walk of AI and data privacy. Unlock the power of your data, from identifying and mitigating privacy risks to fostering trust with users and ensuring responsible AI development.

1Comprehensive Data Discoveryand Classification

Comprehensive Data Discovery and Classification

Unidentified PII (Personally Identifiable Information) and PHI (Protected Health Information) within training data can lead to biased AI models perpetuating discrimination.

Minimizing AI Bias & Ensuring Data Fairness with Zubin

Zubin’s metadata and content Analytics uncover sensitive data, ensuring a comprehensive search across structured and unstructured formats. This prevents AI bias by eliminating hidden sources of discrimination.

2Multi-Layered Risk Assessmentand Prioritization

Multi-Layered Risk Assessment and Prioritization

Balancing robust data security with the need for AI models to access relevant data for training and analysis can be challenging.

Balancing Privacy with AI Innovation with Zubin

Zubin’s risk exposure insights assigns risk scores to sensitive data, considering data type and intended use. Statistical sampling efficiently assesses overall risk without overwhelming resources.

3Data Lineage and Audit Trailfor Regulatory Compliance

Data Lineage and Audit Trail for Regulatory Compliance

Regulations like GDPR and CCPA require organizations to demonstrate responsible data handling practices for AI models.

Demonstrating Responsible AI Practices with Zubin

Zubin’s data usage & traceability keeps a watchful eye on your data throughout the AI lifecycle. It meticulously records which data was accessed, by whom, and for what specific purpose. This ensures compliance with GDPR and CCPA requirements.

4Data-Centric Security with RBACDown to the Data Owner Layer

Data-Centric Security with RBAC Down to the Data Owner Layer

Insufficient access controls and data sharing practices can lead to unauthorized access and potential misuse of data for AI training.

Minimizing Insider Threats & Data Sharing Control with Zubin

Zubin’s RBAC (role-based access control) empowers data owners with granular control, defining access for users and AI models. Secure data sharing capabilities facilitate collaboration while protecting sensitive information.

5Data Wrangling andCuration for Responsible AI

Data Wrangling and Curation for Responsible AI

Poor data quality and inherent biases within training data can lead to inaccurate and unfair AI models.

Ensuring Data Quality & Mitigating Algorithmic Bias with Zubin

Zubin empowers data scientists and data owners to work together on cleaning and transforming data for AI projects. This intuitive suite includes data discovery & classification, anomaly detection, and even helps identify sensitivity within your data. This ensures trustworthy and reliable AI models.

6Data Security Orchestration& AI Model Explainability

Data Security Orchestration & AI Model Explainability

Maintaining ongoing data security for AI models and ensuring their explainability to stakeholders can be challenging.

Continuous Monitoring & Building Trust with Zubin

Zubin doesn’t stop at finding your data – it empowers you to secure it too. Its data security orchestration, automation, and actionability monitors data access patterns, detecting potential threats. data observability and root cause analysis identify anomalies, building trust in AI models.

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