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Data Mesh: Delivering Data-Driven Value at Scale
Ready to dive deeper?
We’ve compiled exclusive Data Mesh content, including on-demand talks, panel discussions featuring Zhamak Dehghani, Founder of Data Mesh, and more!
What is Data Mesh?
Data Mesh – an approach founded by Zhamak Dehghani – refers to a decentralized, distributed approach to enterprise data management. It is a holistic concept that sees different datasets as distributed products, orientated around domains. The idea is that each domain-specific dataset has its own embedded engineers and product owners to manage that data and its availability to other teams, driving a level of data ownership and responsibility, which is often lacking in the current data platforms that are largely centralised, monolithic, and often built around complex pipelines.
Data Mesh is founded around four core principles:
Data as a product
Self-serve infrastructure as a platform
Federated computational governance
Introduction to Data Mesh
In this introduction to Data Mesh, Zhamak Dehghani gives a high-level overview of the concept, which is a paradigm shift that draws from modern distributed architecture considering domains as the first-class concern, applying platform thinking to create self-serve data infrastructure, and treating data as a product.
How to Build a Foundation for Data Mesh: A Principled Approach
In this session, Zhamak Dehghani gives an in-depth explanation of how to apply Data Mesh to your current architecture, following four principles: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a platform, and federated computational governance.
What Data Mesh Means for Data Analysts
What does data mesh actually mean for data analysts? In this panel discussion moderated by moderated by Sean Zinsmeister, VP Product Marketing at ThoughtSpot, panelists Zhamak Dehghani, founder of the term Data Mesh, Daniel Abadi, Darnell-Kanal Professor of Computer Science at University of Maryland, College Park, and Gareth Stevenson, Director, Senior Quantitative Analyst, Bank of America share an interesting mix of perspectives.
More Resources
SQL is Your Data Mesh API
This blog describes why an externalized query service, like Starburst, and a data access control tool, like Immuta provide the perfect framework to enable data mesh.
Data Mesh: The Answer to the Data Warehouse Hypocrisy
Computer Science Professor Daniel Abadi shares his perspective on the Data Mesh and it’s effectiveness and application in relation to the Data Warehouse architecture.
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes Beyond the Data Lake
Check out Data Mesh in practice in this talk from the Databricks AI Summit 2020 which follows our customer Zalando’s journey from a centralized Data Lake to a distributed Data Mesh architecture backed by Spark and built on Delta Lake.
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