Data-centricity

Data-centricity refers to managing data as a primary asset independent of applications. This approach aligns with ISO/IEC 27701 and GDPR principles, ensuring data-level security, privacy, and governance. Unlike traditional application-centric models where data-specific controls are fragmented, a data-centric approach centralizes control,-allowing security policies to follow the data itself regardless of the platform. This is critical for compliance with the GDPR's principle of accountability and the Taiwan Personal Data Protection Act's requirements for data-specific protection measures. It ensures that sensitive information remains protected even as it moves through various systems and processes, reducing the risk of unauthorized access and data-related regulatory violations.

Implementation typically follows three steps: first, Data Classification—categorizing data based on sensitivity as per ISO 27701; second, Data Governance Framework establishment—defining ownership, usage rights, and lifecycle policies; and third, Data-level Security Controls—deploying encryption, masking, and access-level controls. A global retail firm implemented this by centralizing customer data-centricly, achieving a 35% reduction in data-related compliance risks within one year. Key performance indicators (KPIs) include: reduction in data duplication by 25%, increase in data-handling audit coverage to 100%, and a 40% decrease in data-related regulatory fines. These metrics provide a clear ROI for data-centricity investments.

Taiwan enterprises face three primary challenges: 1. Application-centric legacy thinking, where security is tied to systems rather than data; 2. Data Silos, where departments refuse to share or standardize data formats; and 3. Limited compliance expertise for the Taiwan Personal Data Protection Act. To overcome these, enterprises should: A) Appoint a Chief Data Officer (CDO) to lead the initiative; B) Implement a unified Data Catalog to be used across all departments; and C) Invest in automated data-tagging technologies. The priority should be: Phase 1 (Month 1-3) — Data Inventory & Classification; Phase 2 (Month 4-6) — Policy & Tooling; Phase 3 (Month 7+) — Continuous Monitoring. This roadmap typically results in a 50% improvement in data-handling efficiency within the first year.

Winners Consulting Services Co., Ltd. specializes in Data-centricity for Taiwan enterprises, delivering compliant management systems within 90 days. Free consultation: https://winners.com.tw/contact