Data Mesh
A decentralized approach to data architecture where domain teams own and manage their own data as products, rather than centralizing all data in a single warehouse or lake.
Why It Matters
Data mesh addresses the bottleneck of centralized data teams by distributing data ownership to domain experts who best understand the data.
Example
Instead of one central data team managing all company data, the sales team manages sales data, marketing manages campaign data, and each publishes data products for others.
Think of it like...
Like Wikipedia versus a traditional encyclopedia — distributed authorship by domain experts, with shared standards for quality and discoverability.
Related Terms
Data Governance
The overall management of data availability, usability, integrity, and security in an organization. It includes policies, standards, and practices for how data is collected, stored, and used.
Data Engineering
The practice of designing, building, and maintaining the systems and infrastructure that collect, store, and prepare data for analysis and machine learning.
Data Lake
A centralized repository that stores vast amounts of raw data in its native format until needed. Data lakes accept structured, semi-structured, and unstructured data at any scale.
Data Warehouse
A structured, organized repository of cleaned and processed data optimized for analysis and reporting. Unlike data lakes, data warehouses store data in defined schemas.