Data Linkage

Data linkage is the process of connecting records from different data sources that correspond to the same individual or entity. This is achieved by matching common identifiers. Originating in epidemiology and social sciences, it is now widely used in business analytics. In risk management, data linkage is considered a high-risk processing activity as it can reveal sensitive information and enable detailed profiling. Under GDPR Article 35, a Data Protection Impact Assessment (DPIA) is often mandatory before performing large-scale data linkage. This process must adhere to core principles like purpose limitation and data minimization (GDPR Art. 5). It differs from data aggregation, which combines data into statistical summaries without linking records at an individual level, thus posing a lower privacy risk.

Enterprises must embed robust risk management processes when applying data linkage. Key implementation steps include: 1. **Risk Assessment & Legal Basis:** Conduct a Data Protection Impact Assessment (DPIA) per GDPR Art. 35 to identify and mitigate privacy risks like re-identification. Secure a valid legal basis for processing under GDPR Art. 6, such as explicit consent. 2. **Implement Privacy Enhancing Technologies (PETs):** Before linkage, apply techniques like pseudonymization, as recommended in the ISO/IEC 29100 privacy framework, to replace direct identifiers. This minimizes the impact of a potential data breach. 3. **Establish Governance & Monitoring:** Implement strict access controls based on the principle of least privilege and maintain detailed audit logs of all linkage activities. A Taiwanese FinTech company, for example, used this process to link user data for credit scoring, successfully raising its compliance rate to 99% and passing regulatory audits.

Taiwanese enterprises face three main challenges with data linkage: 1. **Regulatory Ambiguity:** Taiwan's Personal Data Protection Act (PDPA) lacks clear definitions for 'de-identification' and 'use beyond original purpose' compared to GDPR, creating legal uncertainty. Solution: Adopt the stricter GDPR standard of anonymization as a best practice and proactively conduct DPIAs to demonstrate due diligence. 2. **Talent and Technology Gap:** There is a shortage of local experts skilled in advanced Privacy Enhancing Technologies (PETs), which are crucial for balancing data utility and privacy. Solution: Partner with external consultants like Winners Consulting for mature solutions and invest in targeted employee training programs. 3. **Organizational Data Silos:** Departmental resistance to data sharing often hinders linkage projects, preventing the organization from realizing the full value of its data. Solution: Form a top-management-sponsored data governance council to create and enforce a unified data sharing policy, led by a Data Protection Officer (DPO).

Winners Consulting specializes in data linkage for Taiwan enterprises, delivering compliant management systems within 90 days. Free consultation: https://winners.com.tw/contact