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.
A Closer Look at What Makes Us Stand Out
Features
Enterprise Risk Posture and Infra Usage Business Intelligence and Reporting
Executive dashboards and reports providing risk and data usage analysis across the enterprise, business units, LOBs, and geographies, complemented by action plans and real-time status updates.
Data Risk and Usage Reporting and Actionability by Team and Data Ownership
Metadata Analytics
Content Analytics
Data Classification
Statistical Sampling
Risk Exposure Insights
Data Containment and Isolation
Quarantining of high-risk sensitive data in secure storage, such as file shares on storage resources or object storage buckets, enhancing data security (lock).
Access Control and File Re-permissioning
Data Policy Creation and Workflow
Personalized data workflows
based on corporate governance
and compliance policies.
Data Sharing
Cloud Integrated Risk Controls
Retention Compliance
Data Redundancy
Self-Service Data Classifications and Migrations
Policy-driven automated data movement, including migration, replication, transform & sync, and archiving across various softwares, both on-premises and in the cloud - SMB, NFS, AWS S3 and OneDrive (File to File, File to Object, Object to Object).
Data Archival
File preservation by converting files into object format by archiving while enabling efficient retrieval via software or RESTful API, audit, and legal discovery, and allowing S3/NFS/SMB-compliant access for compatibility and ease of use.
Data Transformation
Facilitates archival, retrieval, and bidirectional conversion (file to object and object to file) with data quarantine capabilities (transform related).
Data Tiering and Placement
Your Data, Your Rules.
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Zubin in Action
Use cases
Visibility Into Existing Unstructured Data Footprint Across All Data Constituents
Risk Identification of Data Exposure With Actionable Resolution
Privacy Management With Intelligent Data Classification for AI Models
Ensuring Data
Sovereignty Across
Global Data Footprint
Data Owner
Empowerment To View
and Act On Their Data
Storage Optimization
and LCM Across Hybrid
Cloud Infrastructure
Self-Service
Data Classifications
and Migrations
Policy-Based Transfer
of Data Ownership To
Avoid ‘Orphan’ Data
Data Dynamics in the Spotlight
News, events, and articles
Your Guide to What’s Next
Insights, Strategies, and Trends to Keep You in the Know
IDC Spotlight Paper – Rethinking Data Security: Improving Privacy and Compliance with a Shared Approach
From the Heart of the CEO: Zubin, Leading the Future of AI-Driven Self-Service Data Management
IDC Spotlight Paper – Rethinking Data Security: Improving Privacy and Compliance with a Shared Approach
From the Heart of the CEO: Zubin, Leading the Future of AI-Driven Self-Service Data Management
Empowering Data Control and Democratization in the Age of AI
Data Quality: A Persistent and Dynamic, Ever-Evolving Challenge, Not Just a One-Time Fix
Navigating the Ethical Landscape of AI in the Modern Age
Empowering Data Control and Democratization in the Age of AI
Data Quality: A Persistent and Dynamic, Ever-Evolving Challenge, Not Just a One-Time Fix
Navigating the Ethical Landscape of AI in the Modern Age
Do More with Zubin
Related Capabilities