A Data Mesh seamlessly integrates with cloud computing, making it an ideal choice for enterprises seeking to harness the cloud for effective data management. Firstly, cloud resources are available on-demand, empowering Data Mesh to effortlessly accommodate expanding data volumes.
Moreover, cloud providers offer a range of managed services, including managed data warehouses, governance tools and infrastructure provisioning, alleviating the data management burden on individual business domains.
What’s more the core component of a Data Mesh architecture, known as central services, embodies the technologies and processes essential for establishing a self-service data platform featuring federated computational governance in the cloud.
Within the management domain-agnostic data, functionalities are dedicated to provisioning the requisite software stacks for data processing and storage. These software stacks constitute the foundation of the data platform, which will be utilized by various domain teams. Central services implement a solution facilitating the creation of necessary resources for each team to manage their specific stack.
Moreover, cloud self-service data stacks encompass a standardized infrastructure accessible to every team. This infrastructure includes storage subsystems (such as object storage, databases, data warehouses, big data and not only central data lakes), data pipeline tools for importing data from raw sources and ELT (Extract, Load, Transform) tools.
In the realm of management, federated computational governance in the cloud plays a pivotal role. It ensures adherence to access controls, facilitates data classification for regulatory compliance, and enforces policies related to data quality and governance standards. Moreover, it provides centralized data platform monitoring, alerting and metrics services tailored to the needs of organizational data users.