A recent survey by Databricks found that 42% of data professionals are actively working on or planning to implement a Data Mesh architecture in their organizations. This demonstrates the growing interest and recognition of the importance of decentralized, domain-driven data architectures in today’s data-driven world.
“Data Mesh is a data architecture approach that distributes ownership of data to domain-specific teams, treating data as a product, and using standardized tools for seamless integration and data discovery.”
Data Mesh is a relatively new approach to designing and managing data architecture in large, complex organizations. The Data Mesh concept was first introduced by Zhamak Dehghani, a principal consultant at ThoughtWorks, in 2020.
At a high level, Data Mesh is a framework that aims to shift the focus of data architecture from centralized, singular systems to distributed, domain-driven systems that are owned and operated by individual business units.
The Data Mesh architecture approach can benefit various industries, but it is especially useful in industries where data is at the core of their business processes, products, and services.
Industries include:
- Finance
- Healthcare
- E-commerce
- Logistics
- Manufacturing
In e-commerce, logistics, and manufacturing, where the speed and agility of data-driven decision making are critical to staying ahead of competitors, Data Mesh can provide a more decentralized approach to data ownership and management, empowering domain-specific teams to create and deliver data products more efficiently and effectively.
The goal of Data Mesh is to create a more agile, scalable, and resilient data architecture that can keep up with the ever-increasing demand for data-driven insights in today’s business environment.