Data Mesh is an analytical data architecture and operating model where data is treated as a product, leveraging a domain-driven and self-serve design. ## The four principles of Data Mesh 1. **Domain Ownership**: Arranging Data in Domains and declaring full end-to-end ownership 2. **Data as a Product**: Applying Product-thinking to Data Assets and bridging the gap between Producers and Consumers 3. **Self-serve Data Platform**: Removing the intricacies of Infrastructure provisioning to enable domain autonomy and shorten lifecycles 4. **Federated Computational Governance**: Seeking interoperability through global standardization ## Data Mesh Advantages - Better Data Governance - Improved Data Quality - Data Products are built thinking on the consumer's needs first - Fine-grained Access by Domain ## Data Mesh Disadvantages - The decentralization of data is challenging. It requires changes not only technically, but also at organizational and mindset levels. %% wiki footer: Please don't edit anything below this line %% ## This note in GitHub <span class="git-footer">[Edit In GitHub](https://github.dev/data-engineering-community/data-engineering-wiki/blob/main/Concepts/Data%20Architecture/Data%20Mesh.md "git-hub-edit-note") | [Copy this note](https://raw.githubusercontent.com/data-engineering-community/data-engineering-wiki/main/Concepts/Data%20Architecture/Data%20Mesh.md "git-hub-copy-note")</span> <span class="git-footer">Was this page helpful? [👍](https://tally.so/r/mOaxjk?rating=Yes&url=https://dataengineering.wiki/Concepts/Data%20Architecture/Data%20Mesh) or [👎](https://tally.so/r/mOaxjk?rating=No&url=https://dataengineering.wiki/Concepts/Data%20Architecture/Data%20Mesh)</span>