> For the complete documentation index, see [llms.txt](https://v2.dataos.info/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://v2.dataos.info/references/interfaces/apis/data-product-apis.md).

# Data Product APIs

Explore the Data Product API surface for governed discovery, queries, reusable results, and operational insights.

Build governed applications and workflows directly on a Data Product. Discover its semantic contract, query approved business definitions, publish reusable perspectives, inspect quality and activity, and integrate through one versioned API.

## Start here

* [Getting started](/references/interfaces/apis/data-product-apis/getting-started.md): authentication & authorization, API calls, and error handling.
* [Querying Data Products](/references/interfaces/apis/data-product-apis/querying-data-products.md): REST, Semantic SQL, GraphQL, Metrics, Perspectives, and advanced query behavior.
* [SDKs](/references/interfaces/apis/data-product-apis/sdks.md): Python and TypeScript clients.
* [API reference](/references/interfaces/apis/data-product-apis/api-reference.md): endpoint-level request and response contracts.

## Choose the right layer

The guides explain **which interface to use and how to form a correct query**. The API reference documents **every endpoint and wire field**. Keep business-facing integrations on semantic interfaces; use physical Source SQL only as a deliberate escape hatch.

From a Data Product, select **Activate → APIs** to open the in-product API experience and download its generated Postman collection.


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://v2.dataos.info/references/interfaces/apis/data-product-apis.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.