This white paper proposes a comprehensive Data Protection Impact Assessment (DPIA) framework for the Data Warehouse, detailing the potential commercial and personal data risks across individual data marts—including Projects, Employee, and Customer—and introducing a “Defence by Design” methodology to mitigate these risks effectively.
Objectives
- Identify Risks: Analyse the specific data privacy risks associated with each Data Mart.
- Defence by Design: Outline proactive methodologies to embed data protection and security into the architecture and operations of the Data Warehouse.
- Governance Framework: Establish a standardised DPIA template to be reused for future data marts or integrations.
Data Marts Overview and Risk Assessment
1. Projects Data Mart
- Purpose: Tracks project costs, revenue, and value, including sensitive commercial and operational data.
- Risks:
- Exposure of project financials or strategic information.
- Leakage of customer or vendor contractual details.
- Unauthorised access to internal project performance metrics.
- Potential Impact: Financial loss, reputational damage, legal penalties.
2. Employee Data Mart
- Purpose: Manages employment details, including personal and contractual data.
- Risks:
- Exposure of sensitive personal identifiers (e.g., NI numbers, employment agreements).
- Unauthorised visibility of performance or disciplinary records.
- Breaches of GDPR or local data protection laws.
- Potential Impact: Privacy violations, regulatory fines, loss of employee trust.
3. Customer Data Mart
- Purpose: Stores customer information for invoicing, communication, and service delivery.
- Risks:
- Loss of personal data, such as addresses, payment details, or identifiers.
- Processing errors leading to incorrect invoicing or communications.
- Exposure of sensitive transactional data.
- Potential Impact: Customer dissatisfaction, legal non-compliance, reputational harm.
Defence by Design Methodology
1. Data Minimisation
- Ensure data marts only hold the fields essential for their function.
- Use techniques such as pseudonymisation and tokenisation for personal identifiers.
2. Access Control
- Implement role-based access controls (RBAC) and data masking to restrict visibility based on user roles.
- Monitor and log all data access actions to ensure accountability.
3. Encryption
- Use end-to-end encryption for data at rest and in transit.
- Enforce strict encryption key management practices.
4. Audit and Monitoring
- Regularly audit data marts for unused or stale data and remove it promptly.
- Deploy real-time monitoring for unusual access patterns or unauthorised queries.
5. Privacy by Design Frameworks
- Align data architecture with GDPR’s “privacy by design and by default” principle.
- Conduct DPIAs during the initial design phase of each data mart and update them periodically.
6. Incident Response Plan
- Develop and test response protocols for data breaches, including communication strategies for stakeholders.
- Integrate automated alerts for detecting and responding to potential threats.
Implementation and Governance
- DPIA Template: Develop a reusable DPIA template that includes:
- Data inventory and classification.
- Risk identification and assessment.
- Mitigation strategies and actions.
- Training and Awareness: Provide training for teams on DPIA processes, privacy principles, and handling sensitive data.
- Stakeholder Engagement: Regularly engage stakeholders, including data governance teams, legal advisors, and IT, to ensure alignment with organisational priorities and compliance requirements.
- Continuous Improvement: Use lessons learned from DPIA reviews and incidents to refine the Defence by Design methodology and adapt to new risks.