Data Security Platforms

1. Click red button below: Book a briefing. You will be directed to the Office365 calendar tool.
2. Select Leadership Compass Briefing 55 mins
3. Select Alexei Balaganski
4. Choose date and time between June 10th - July 3rd
5. You will receive a Teams invite
6. Please prepare a slide deck and provide it to the analyst

Briefing Outline - Recommended Structure

1. Company and Product Context (5 minutes)

• Brief company overview and positioning in the Data Security Platforms market
• Product scope and major components relevant to this Leadership Compass
• Primary customer profiles and deployment scenarios

2. Architecture and Deployment Model (10 minutes)

• Supported delivery models (SaaS, self-managed, hybrid)
• Scalability across multi-cloud, SaaS, and on-premises data environments
• Supported data sources (databases, data lakes, SaaS apps, etc.)
• Integration with identity providers, data platforms, and cloud services
• Agent-based versus agentless approaches to data access and monitoring
• Handling of structured and unstructured data environments

3. Core Capabilities (Aligned with Evaluation Criteria)

Please structure this section explicitly around the evaluation categories below. We do not expect every solution to cover all capabilities, so please focus on those you do support. You do not need to cover every feature exhaustively, but clarity and technical depth are essential.

• Data Discovery and Classification: Identification and classification of sensitive data across environments, including structured and unstructured sources
• Data Security Posture Management: Detection of misconfigurations, excessive permissions, and data exposure risks across data stores and pipelines
• Data Protection: Encryption, tokenization, masking, and other controls applied to data at rest, in transit, and in use
• Access Management for Data: Fine-grained, identity- and attribute-based access controls for data, including least privilege and just-in-time access
• Monitoring and Analytics: Visibility into data access and usage, behavioral analytics, anomaly detection, and risk scoring
• Attack Prevention and Response: Detection and prevention of data exfiltration, insider threats, and misuse, including policy enforcement and automated response
• Audit and Compliance: Logging, reporting, and support for regulatory frameworks such as GDPR, HIPAA, PCI DSS, etc.
• Performance and Scalability: Handling of large-scale data environments, latency impact, and architectural limits
• User and Developer Experience: Administrative usability, policy definition workflows, APIs, SDKs, and automation capabilities
• Integration and Ecosystem Interoperability: Integration with SIEM, SOAR, IAM, DevOps pipelines, and cloud-native platforms
• AI and Data Governance: Controls for protecting sensitive data in AI pipelines, including training data governance, inference controls, and access policies for AI agents and services

4. Demonstration (Mandatory, at least 20 minutes)

• Management console, onboarding of data sources, and classification workflows
• Policy definition and enforcement for data access and protection
• Realistic scenarios for detecting and responding to data risks
• Monitoring, analytics, and investigation workflows
• AI-related capabilities, where applicable

The demo should reinforce previously presented capabilities, not introduce entirely new concepts. Focus on differentiating features and realistic workflows. Please use a demo environment with meaningful data volume and complexity.

5. Differentiation and Roadmap (5–10 minutes)

• Clear articulation of what differentiates your platform from peers
• Near-term roadmap priorities relevant to Data Security Platforms
• Known limitations or trade-offs (openness is appreciated and expected)

6. Wrap-Up and Q&A

• Reference customers, deployments, or representative use cases
• Time for clarification questions and discussion

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