# Importing training data


**Note**  
You can only supply a training data set for using in a Clean Rooms ML lookalike model that has data stored in Amazon S3. However, you can supply the seed data for a lookalike model using SQL that runs across data stored in any supported data source. 

Before you create a lookalike model, you must specify the AWS Glue table that contains the training data. Clean Rooms ML doesn't store a copy of this data, just metadata that allows it to access the data.

**To import training data in AWS Clean Rooms**

1. Sign in to the AWS Management Console and open the [AWS Clean Rooms console](https://console.aws.amazon.com/cleanrooms/home) with your AWS account (if you haven't yet done so).

1. In the left navigation pane, choose **AWS ML models**.

1. On the **Training datasets** tab, choose **Create training dataset**.

1. On the **Create training dataset** page, for **Training dataset details**, enter a **Name** and optional **Description**.

1. Choose the **Training data source** by selecting the **Database** and **Table** that you want to configure from the dropdown lists.
**Note**  
To verify that this is the correct table, do either one of the following:  
Choose **View in AWS Glue**.
Turn on **View schema** to view the schema.

1. For **Training details**, choose the **User identifier column**, **Item identifier column**, and **Timestamp column** from the dropdown lists. The training data must contain these three columns. You can also select any other columns that you want to include in the training data.

   The data in the **Timestamp column** must be in the Unix epoch time in seconds format.

1. (Optional) If you have any **Additional columns to train**, choose the **Column name** and **Type** from the dropdown lists.

1. In **Service access**, you must specify a service role that can access your data and provide a KMS key if your data is encrypted. Choose **Create and use a new service role** and Clean Rooms ML will automatically create a service role and add the necessary permissions policy. Choose **Use an existing service role** and enter it in the **Service role name** field if you have a specific service role that you want to use.

   If your data is encrypted, enter your KMS key in the **AWS KMS key** field, or click **Create an AWS KMS key** to generate a new KMS key.

1. If you want to enable **Tags** for the training dataset, choose **Add new tag** and then enter the **Key** and **Value** pair. 

1. Choose **Create training dataset**. 

For the corresponding API action, see [CreateTrainingDataset](https://docs.aws.amazon.com/cleanrooms-ml/latest/APIReference/API_CreateTrainingDataset.html).