> For the complete documentation index, see [llms.txt](https://docs.jentis.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.jentis.com/raw-data-exports.md).

# Raw Data Exports

In the dynamic world of online data management, JENTIS stands out with its innovative approach to tag management and data capturing. A notable addition to our suite of tools is the "Raw Data" feature. This tool revolutionizes traditional tag management by not only routing and streaming data but also providing the unique capability to store and access raw traffic data directly on the platform.

## Raw Data Tool Overview <a href="#jentisrawdatatool-rawdatatooloverview" id="jentisrawdatatool-rawdatatooloverview"></a>

The Raw Data tool by JENTIS is designed to capture, store, and provide access to the raw, unprocessed traffic data of a website. This enables a more granular analysis of user interactions, offering insights far beyond traditional analytics.

## Data Storage Capability <a href="#jentisrawdatatool-datastoragecapability" id="jentisrawdatatool-datastoragecapability"></a>

Unlike standard tag management systems that focus solely on data routing, JENTIS’s Raw Data tool offers onboard storage capabilities. This means data is not just passed through but is stored within the JENTIS platform. Storing data on the platform allows for more extensive historical analysis and the ability to revisit and reprocess data as needed.


---

# 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://docs.jentis.com/raw-data-exports.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.
