> ## Documentation Index
> Fetch the complete documentation index at: https://futureagi.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Create Dynamic Column by Extracting JSON

> The **Extract JSON Key** feature allows users to extract specific values from JSON-formatted data stored in a dataset of JSON data type column.

## **1. Select a Dataset**

Before configuring retrieval, ensure you have selected a dataset. If no dataset is available, follow the steps to **Add Dataset** on the Future AGI platform.

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## **2. Accessing the JSON Extraction Interface**

To configure JSON key extraction, navigate to your dataset and click the + **Add Columns** button in the top-right menu. Scroll down to the **Dynamic Columns** section and select **Extract JSON Key** to open the setup panel.

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## **3. Configuring JSON Key Extraction**

* **Name**: Assign a meaningful name to the new column where the extracted data will be stored.

* **Column**: Select the dataset column of JSON data type that contains structured key-value pairs.

* **Enter JSON Path**: Provide the **exact key (header) name** from the JSON structure. The system will retrieve the corresponding value from each row and populate it in the new column.
  * Example JSON for one of the row of JSON datatype column:

    ```json theme={null}
    {
      "name": "John Doe",
      "age": 30,
      "city": "New York"
    }
    ```

  * If the user enters `"age"` as the JSON key, the new column will extract and display the value from each row containing similar JSON data.

* **Concurrency**: Define how many rows should be processed simultaneously.

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After configuring the settings, click **Test** to preview the extracted values. If the results appear accurate, click **Create New Column** to finalise the extraction. The newly created column will dynamically update with values retrieved from the specified JSON key.

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## **Best Practices for JSON Extraction**

* **Ensure the selected column contains valid JSON data** with consistent formatting.
* **Use precise key names** as they appear in the JSON structure to avoid extraction errors.
* **Select concurrency settings** based on dataset size to balance speed and performance.

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