# Data Mapper
This lets you transform data between steps. You can map data from previous steps, variables, or secrets into a new object format you need later in the flow.
For example,
This example mapping step titled "**Content"** can be used when you need to map data (usually text) from a previous step and ensure it’s passed forward as a string.
### **Params mapped in configuration**
```
res = steps.chatGPT.output.choices[0].message.content
```
* Here, `res` is the variable inside the Content step.
* It is mapped directly from the **ChatGPT connector’s** output: `steps.chatGPT.output.choices[0].message.content`.
* The mapped value must always resolve to a **string** type, since Content steps are designed to pass textual data forward.
### **Example**
* Pass the response from ChatGPT as plain text into another step (e.g., a database insert, a file generator, or a Slack notification).
To make this easier, the **AI agent** in the top-right corner offers smart suggestions for mapping your data. It helps you quickly pull values from previous steps or any flow data. You can simply drag and drop items like **Headers**, **Inputs**, **Steps**, **Secrets**, or **App Config** into the field you want to configure; making your mappings faster, more accurate, and less manual.
You can map values either in JSON, JavaScript, C#, Form, or Python Lambda.
### **Example JSON Mapping**
```
{
"json": {
"res": "{{data.steps.chatGPT.output.choices[0].message.content}}"
},
"actions": {
"json": {
"action": [],
"targetType": "object"
},
"json.res": {
"action": [],
"targetType": "object"
}
}
}
```
> You can learn more about Data Mapping in Flows [here](https://docs.fastn.ai/building-flows/flow-setup-essentials/data-mapping-in-flows).
