Understanding data mesh in public sector: Pillars, architecture, and examples

Public sector agencies face challenges in managing vast and distributed datasets, often resulting in data silos that impede real-time and efficient data access. Data mesh offers a solution by decentralizing data management, empowering domain-specific teams to take ownership of their data, and treating datasets as products with clear documentation and quality standards. It enables more efficient data handling and governance through self-service platforms and federated governance, allowing data to be accessed and analyzed securely and swiftly across various domains. Unlike data lakes and data fabrics that can lead to silos or require data duplication, data mesh provides a unified, searchable platform that democratizes data access and enhances AI-driven operations. Its architecture supports a user-centric approach, improving collaboration and decision-making in sectors such as defense, public health, and transportation. Elastic, an analytics platform, exemplifies this approach by offering features like cross-cluster search and role-based access control, thus maximizing data value for government, healthcare, and education sectors.