Data Modeling
Data Modeling is the discipline of designing structured representations of data to organize information, define relationships, and govern how data is stored, accessed, and managed. It spans conceptual, logical, and physical models across relational, dimensional, NoSQL, graph, and data vault paradigms, supported by standards and tools from the OMG, DAMA, Erwin, PowerDesigner, dbt, and modern data modeling platforms.
Data Modeling is tracked in the API Evangelist network. This page is the human-readable profile that sits on top of the machine-readable index we maintain at apis.io.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Data Modeling is in the network as a tracked entity. We haven't yet indexed a public API surface for it — when one is published, the artifacts, score, and agent-readiness read will appear here automatically. The source repository is where that profile is built.
← All providers · Data indexed from github.com/api-evangelist/data-modeling · machine-readable index on apis.io