Practice data mesh platform vocabulary: self-serve data infrastructure, product scaffolding, compute-as-a-service, data catalog discovery, and governance APIs.
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A data mesh design says 'The self-serve data platform abstracts infrastructure.' What does this mean for domain teams?
The self-serve data platform is the fourth principle of data mesh. It provides infrastructure capabilities as a service so domain teams can focus on data, not plumbing. Teams get pre-built pipeline templates, managed compute, and automated deployment — like an internal PaaS for data products.
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Your platform team says 'We provide data product scaffolding.' What does scaffolding mean in this context?
Data product scaffolding is the platform team's equivalent of a project generator — running a command creates a standardized data product skeleton with the right folder structure, pipeline framework, schema registry connection, observability hooks, and catalog registration. Teams start building immediately instead of from scratch.
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A platform architecture doc mentions 'the compute-as-a-service layer.' What does this provide to domain teams?
Compute-as-a-service in data mesh means the platform team manages the compute infrastructure. Domain teams declare what compute they need (e.g., 'run this Spark job') and the platform provisions it, handles scaling, and manages lifecycle — freeing domain teams from infrastructure management.
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Your governance framework says 'The data catalog is the discovery layer.' What must the catalog expose to fulfill this role?
For the data catalog to be the discovery layer, it must be the single source of truth for everything a consumer needs: who owns the data, what schema it has, what SLA it commits to, how fresh it is, how to get access, and what lineage it has. An incomplete catalog forces consumers to ask teams directly — defeating the self-serve model.
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Your platform team implements 'a governance API that enforces policies.' What type of policies might a governance API enforce?
A governance API enforces federated computational governance — policies like 'all data products containing PII must declare a data classification' or 'consumer access to sensitive domains requires approval workflow' are enforced automatically via API, not through manual review. This scales governance without a central governance bottleneck.