For over half a century organizations have assumed that data is an asset to collect more of, and data must be centralized to be useful.
These assumptions have led to centralized and monolithic architectures, such as data warehousing and data lake, that limit organizations to innovate with data at scale.
Data Mesh is an alternative sociotechnical approach in managing analytical data.
Its objective is enabling access to high quality data for analytical and machine learning use cases - at scale.
It's an approach that shifts the data culture, technology and architecture:
- from centralized collection and ownership of data to domain-oriented connection and ownership of data
- from data as an asset to data as a product
- from proprietary big platforms to an ecosystem of self-serve data infrastructure with open protocols
- from top-down manual data governance to a federated computational one.
This is a well-rounded introductory talk to Data Mesh. Why you might need one, what it is and how to get started with implementing it.