> 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/consume/activate.md).

# Activate

- [Activate a Data Product](https://v2.dataos.info/consume/activate/overview.md): Choose the path to consume a Data Product: BI tools, SQL clients, APIs, or AI.
- [Querying Data Products](https://v2.dataos.info/consume/activate/querying-data-products.md): How querying a Data Product works, and where each query path leads.
- [BI tools](https://v2.dataos.info/consume/activate/bi-tools.md): Use Data Products in BI and analytics tools such as Power BI and Tableau Desktop.
- [Tableau Desktop](https://v2.dataos.info/consume/activate/bi-tools/tableau.md): Connect Tableau Desktop to turn your dimensions and measures into charts, dashboards, and drill-downs - no SQL required.
- [Tableau Cloud](https://v2.dataos.info/consume/activate/bi-tools/tableau-cloud.md): This guide covers connecting Tableau Cloud to Data Products, publishing semantic models, and creating workbooks.
- [Power BI Desktop](https://v2.dataos.info/consume/activate/bi-tools/desktop.md): Connect Power BI Desktop to turn your dimensions and measures into charts, dashboards, and drill-downs - no SQL required.
- [Power BI Service](https://v2.dataos.info/consume/activate/bi-tools/service.md): Publish Power BI reports to Power BI Service and connect them to DataOS through an on-premises gateway.
- [APIs](https://v2.dataos.info/consume/activate/apis.md): Connect applications and automation to Data Products with GraphQL, semantic query, metadata, activity, and quality APIs.
- [Collection](https://v2.dataos.info/consume/activate/apis/collection.md): Import the Postman collection for a Data Product and test API requests fast.
- [SDK](https://v2.dataos.info/consume/activate/apis/sdk.md): Build applications and automations on top of Data Product APIs with typed SDKs.
- [Python](https://v2.dataos.info/consume/activate/apis/sdk/python-sdk.md): Install and use the Python SDK for Data Product APIs.
- [TypeScript](https://v2.dataos.info/consume/activate/apis/sdk/typescript-sdk.md): Install and use the TypeScript SDK for Data Product APIs.
- [Data application](https://v2.dataos.info/consume/activate/apis/data-application.md): Register and run an application built on top of a Data Product's APIs.
- [Deploy](https://v2.dataos.info/consume/activate/apis/data-application/deploy.md): Deploy a containerized Data Product application in DataOS using an app Resource.
- [Link](https://v2.dataos.info/consume/activate/apis/data-application/link.md): Surface an externally hosted Data Product application using a link Resource.
- [Database clients](https://v2.dataos.info/consume/activate/database-clients.md): Connect a desktop SQL client to a Data Product and query its semantic models through the MySQL wire protocol.
- [MySQL](https://v2.dataos.info/consume/activate/database-clients/mysql.md): Connect a command-line MySQL client to a Data Product and query its semantic models.
- [Query](https://v2.dataos.info/consume/activate/database-clients/mysql/query.md): Query semantic models with SQL: dimensions, measures, joins, and filters.
- [DBeaver](https://v2.dataos.info/consume/activate/database-clients/dbeaver.md): Connect DBeaver to a Data Product and query semantic models over the MySQL protocol.
- [Reusability](https://v2.dataos.info/consume/activate/reusability.md): Reuse a published Data Product as the input for a new one instead of rebuilding it.


---

# 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/consume/activate.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.