> For the complete documentation index, see [llms.txt](https://help.transform.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.transform.ai/integrations/data-sources.md).

# Data Sources

### Overview

Data sources provide reference inputs that improve scope quality and reporting consistency.

A clear source-of-truth model reduces conflicting updates across systems.

### Key Concepts

* **Source of truth**: system responsible for the authoritative value
* **Reference dataset**: upstream data used for lookups, identifiers, or classifications
* **Mapping**: alignment from source fields to Transform fields

### How It’s Used

Use data sources to seed Projects with consistent Systems, Processes, and reference lists.

Use them to keep identifiers consistent for cross-system reporting.

### Benefits

* Reduced duplicate and inconsistent records
* Cleaner reporting through stable identifiers
* Faster onboarding through reusable reference datasets

### Setup Steps

{% stepper %}
{% step %}

### Define the source-of-truth model

Define which system owns:

* identifiers
* ownership and teams
* status signals
* reference lists, such as Systems and classifications
  {% endstep %}

{% step %}

### Map into Transform concepts

Map source data into:

* Systems and System Types
* Processes and Process Hierarchy
* Segment Types and Segments (Organization scope)
  {% endstep %}

{% step %}

### Validate data quality

1. Confirm required fields are populated.
2. Confirm naming conventions match governance standards.
3. Create Save Views that surface missing or inconsistent values for cleanup.
   {% endstep %}
   {% endstepper %}

### Best Practices

* Keep mappings documented and versioned.
* Avoid field proliferation without reporting value.
* Standardize Segment Types to protect analytics continuity.

### Summary

Data sources are most valuable when ownership is explicit and mappings are stable.

Related:

* [Connectors](/administration/connectors.md)
* [Blueprints](/blueprints/blueprint-fundamentals.md)


---

# 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://help.transform.ai/integrations/data-sources.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.