Data Mesh
Data Mesh is a modern architectural approach in data management and analytics. It shifts away from traditional centralized data management models (like data warehouses and lakes) and advocates for a decentralized approach.
Here are the key characteristics and principles of Data Mesh:
-
Domain-Oriented Decentralized Data Ownership and Architecture
Data Mesh emphasizes that data should be managed and owned by domain-specific teams (e.g., sales, marketing, logistics) rather than a centralized data team. This approach allows each team to control and optimize their data based on their specific needs and expertise.
-
Data as a Product
Data is treated as a product, with each domain team responsible for the lifecycle of the data products they own. This includes ensuring data quality, reliability, and usability. Data products are built to be discoverable, understandable, trustworthy, and usable by other teams.
-
Self-Serve Data Infrastructure as a Platform
To enable domain teams to manage their data products effectively, a self-serve data platform is provided. This platform offers tools and capabilities for data storage, processing, and analytics, ensuring teams can access and use data with autonomy but without needing to manage complex data infrastructure.
-
Federated Computational Governance
Data Mesh also involves a federated approach to governance. While teams have autonomy over their data, there are overarching guidelines and policies to ensure compliance, security, and interoperability across the organization.
Noted
- Data Mesh in Practice
- Navigating Your Data Platform’s Growing Pains: A Path from Data Mess to Data Mesh
- How Data Mesh Architecture changed our Engineering Teams
- Challenges and Solutions in Data Mesh – Part 1