> 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/get-started/readme.md).

# Consumer journey

Consuming a data product happens in three stages. Discover the right one. Understand whether it's trustworthy. Activate it where you work, whether that is a report, an application, an API, an AI agent, or another Data Product.

## Discover

Find a data product, perspective, or metric that matches a business, analytical, operational, or technical use.

<details open>

<summary><strong>Open the Hub</strong></summary>

From the DataOS home page, select **Products** to open the Hub.

<figure><img src="/files/zh7ehzimkPtb4bQikW1U" alt=""><figcaption></figcaption></figure>

</details>

<details>

<summary><strong>Search</strong></summary>

The Hub lists the Data Products available to you in the selected Tenant. Use search and filters to narrow the list, then open the one that fits. For the full walkthrough, see [Search the Hub](/consume/discover/search-the-hub.md).

![](/files/2H5RVGzrdZixIpWj7Kq9)

</details>

<details>

<summary><strong>Or ask AI</strong></summary>

Ask AI in natural language to find a Data Product, Metric, or Perspective based on your business need. For example prompts and results, see [Discover with AI](/consume/discover/discover-with-ai.md).

![](/files/ZdcrNmRfj7vn4YoGMNnG)

</details>

## Understand

Confirm the data product is relevant, trustworthy, and fit for the intended use.

<details open>

<summary><strong>Explore the assets</strong></summary>

See what the product contains before you query it or connect it to a tool. Review its inputs, outputs, [models](/consume/understand/assets/semantics.md), and metrics, and trace the lineage between them. For a full walkthrough, see [Explore assets](/consume/understand/assets.md).

![](/files/RLdOWwgIblyhyDSrBSC3)

</details>

<details>

<summary><strong>Check trust and freshness</strong></summary>

Review quality checks, freshness signals, and AI-readiness in [Trust and freshness](/consume/understand/quality.md) so you know what the product is good for.

![](/files/dzt9JxmcAfK3xEAFZYy7)

</details>

<details>

<summary><strong>Look at recent activity</strong></summary>

Review [Track activity](/consume/understand/activity.md) to see run history, version history, errors, and recent plan changes.

![](/files/UXXJKFOxuinJuD3Ol6FQ)

</details>

<details>

<summary><strong>Query in Studio</strong></summary>

Use [Query in Studio](/consume/understand/overview.md) to validate the product through its governed semantic layer. Choose dimensions and measures in the visual builder, then run the query and inspect the result.

<figure><img src="/files/HG3n1RcXnQkSceVXUwWO" alt=""><figcaption></figcaption></figure>

</details>

<details>

<summary><strong>Or ask AI</strong></summary>

Use [Understand with AI](/consume/understand/understand-and-trust-with-ai.md) to summarize health, lineage, ownership, and limitations, then assess whether the product is fit for use.

</details>

## Activate

Use the data product through BI tools, database clients, APIs, AI workflows, or as input to another Data Product.

<details open>

<summary><strong>Open activation options</strong></summary>

Once a product is understood and trusted, use it in your workflow. Re-check freshness, quality, or recent changes when the use case is sensitive to them.

<figure><img src="/files/oFlFNGK0rHl3EjlHQhLY" alt=""><figcaption></figcaption></figure>

</details>

<details>

<summary><strong>Pick an activation path</strong></summary>

These are the main tools and interfaces you can explore to activate the data product.

<table data-view="cards"><thead><tr><th></th></tr></thead><tbody><tr><td><a href="/pages/Zp6H5YAiKzkjYf6A8j7Q"><strong>BI tools</strong></a><br>Build reports and dashboards in Power BI or Tableau Desktop.</td></tr><tr><td><a href="/pages/LyBO1RyM3EvKbz3VR6eE"><strong>APIs</strong></a><br>Query and integrate data through APIs and SDKs.</td></tr><tr><td><a href="/pages/TUHfHehJfkTsDyv6Siee"><strong>Database clients</strong></a><br>Query from a desktop SQL client.</td></tr><tr><td><a href="/pages/Iv7IrhZxYMLqhTFHWRF2"><strong>AI clients</strong></a><br>Connect AI clients and agentic frameworks through Data Product MCP.</td></tr></tbody></table>

</details>


---

# 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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://v2.dataos.info/consume/get-started/readme.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.