> For the complete documentation index, see [llms.txt](https://playbooks.equalexperts.com/data-pipeline/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://playbooks.equalexperts.com/data-pipeline/who-uses-a-data-pipeline.md).

# Who uses a data pipeline?

We are often asked, **‘But you don’t do user analysis for data, do you?’**

### We believe that, as in any software development project, pipelines will only be successful if you understand the needs of the users.

**FOR A DATA PIPELINE, THE USERS ARE TYPICALLY:**

1. **Business Intelligence / Management Information analysts** who need data to create reports.
2. **Data scientists** who need data to do an in-depth analysis of point problems or create algorithms for key business processes (we use ‘data scientist’ in the broadest sense, including credit risk analysts, website analytics experts, etc.).
3. **Process owners** who need to monitor how their processes are performing and troubleshoot when there are problems.

Data users are skilled at visualising and telling stories with data, identifying patterns, or understanding significance in data. They may well have strong statistical or mathematical backgrounds. In most cases, they are accustomed to having data provided in a structured form - ideally denormalised - so that it is easy to understand the meaning of an individual row of data without the need to query separate tables or databases.


---

# 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:

```
GET https://playbooks.equalexperts.com/data-pipeline/who-uses-a-data-pipeline.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.