Data Mesh is a novel approach to managing data at scale that emphasizes domain-driven decentralization and self-serve data platforms. The idea is to create a network of data domains where each domain owns and manages its own data and provides a self-service platform for accessing and sharing data across domains.
- Domain-Driven Decentralization: Data Mesh emphasizes the importance of domain-driven design where each domain has its own data ownership, governance, and access control policies. This approach allows for greater flexibility, scalability, and autonomy for each domain.
- Self-Serve Data Platforms: Data Mesh promotes the creation of self-service data platforms where domain experts can publish, discover, and consume data without relying on central data teams. This approach fosters a culture of data empowerment and decentralization.
- Data as a Product: Data Mesh treats data as a product that needs to be managed and optimized for value creation. This approach requires domain experts to think like product managers and focus on delivering high-quality data that meets the needs of their customers.
- Data Mesh Principles and Logical Architecture by Zhamak Dehghani
- Data Mesh: A Modern Data Architecture for the Enterprise by Zhamak Dehghani
- Data Mesh: Delivering Data-Driven Solutions by Daniel Gillick
Applying Data Mesh to Business
Data Mesh can help businesses overcome the limitations of traditional centralized data architectures by empowering domain experts to manage and share data in a decentralized and self-service manner. By treating data as a product and focusing on delivering high-quality data that meets the needs of various stakeholders, businesses can unlock new opportunities for data-driven innovation and value creation. However, implementing Data Mesh requires a significant shift in mindset and culture, and businesses need to invest in building the necessary infrastructure, governance, and collaboration frameworks to support this approach.