> For the complete documentation index, see [llms.txt](https://docs.mediarithmics.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mediarithmics.io/setup-and-monitor/collect-and-manage-your-data/import-data-in-batch/data-loader/load-profiles.md).
# Load profiles
Map CSV columns to profile properties, with optional transformations.
## Your goal
Create or update user profiles from the properties in a CSV file, mapping columns to schema properties in the interface.
## Expected outcome
Profiles created or updated for the users the file identifies, with only the columns you mapped affected.
## Prerequisites
* A `LIVE` schema with a **top-level field under `UserPoint` named `UserProfile`**. Without it, selecting the profile document type returns an error.
* A CSV file meeting the [file requirements](/setup-and-monitor/collect-and-manage-your-data/import-data-in-batch/data-loader.md#file-requirements).
* The compartment or registry the identifier belongs to.
## Configure the import
Two sections to fill in.
{% tabs %}
{% tab title="Identifier" %}
This is how each row is matched to a user.
* Select the **CSV property** to use as the identifier.
* Choose the **identifier type**: `USER_ACCOUNT`, `USER_EMAIL`, or `USER_DEVICE_TECHNICAL_ID` - and specify the related **compartment** for an account, or **registry** for a device technical ID.
* Optionally select a **hashing** method to apply to the input.
{% hint style="warning" %}
The identifier type decides whether the profile is identified or anonymous:
* **`USER_ACCOUNT`** - the `user_account_id` derived from the CSV property, together with the selected `compartment_id`, is used as the profile identifier.
* **`USER_EMAIL` or `USER_DEVICE_TECHNICAL_ID`** - the profile **remains anonymous**: no `user_account_id`, and the **default compartment** is used as the profile identifier.
{% endhint %}
Only **one hashing method** per field is allowed, and hashing is the only transformation available on identifiers.
{% endtab %}
{% tab title="Profile" %}
For each **CSV property** you want to import, select the corresponding **profile property**. You do not need to configure every column in the file.
Optionally apply one or more **transformations** to the input.
{% hint style="info" %}
If a profile already exists for the user - an existing combination of account and compartment:
* Properties you mapped **override** existing values, or are created if they did not exist.
* Properties you did **not** map are left as they are.
{% endhint %}
{% endtab %}
{% endtabs %}
## Data types in the CSV
The value has to parse as the type of the target property.
| Data type | What is expected | Example |
| --------- | ------------------------------------------------------------ | --------------------------------- |
| Int | An integer with no thousands separator | `54` |
| Float | The dot `.` as decimal separator | `74.32` |
| Date | ISO format with year, month, and day - `YYYY-MM-DD` | `2025-01-04` |
| String | Enclose in double quotes if the value contains the delimiter | `science` / `"science, politics"` |
| Boolean | `true`, `false`, `yes`, `no`, `1`, or `0` | `true` |
| Timestamp | A timestamp in milliseconds | `1742033780000` |
## Available transformations
Which transformations you can apply depends on the type of the target profile property - shown in brackets when you select it.
| Profile property type | Transformations |
| --------------------- | ---------------------------------------------------------------------------- |
| string | `TO UPPER CASE`, `TO LOWER CASE`, `REMOVE SPACES`, `HASH SHA256`, `HASH MD5` |
| date | `REMOVE SPACES`, `AGE TO DATE` |
| int | `REMOVE SPACES`, `DATE TO AGE` |
| boolean | `REMOVE SPACES` |
| float | `REMOVE SPACES` |
| timestamp | `REMOVE SPACES` |
{% hint style="info" %}
`AGE TO DATE` and `DATE TO AGE` are the two transformations that change meaning rather than form - useful when your source stores an age and your schema stores a birth date, or the reverse.
{% endhint %}
## Example file
```csv
Email_sha256,first_name,last_name,age,gender,addr_country,zip_code,subscriber,best_category,LTV
ce5bfa8406dd062b059a4b841bf36de186977fe515dc5a704a58e973cab1a5d5,Salome,Cargon,32,Female,Russia,36987-1612,false,Outdoors,458.04
9980f7e8331dce3bfa2e3b3ab6b69dcb960658bcb400801cece7873afeb5a905,Gene,Pulham,45,Male,Tanzania,68788-9208,true,Jewelry,2894.53
```
## Verify
* The transformation report shows no errors before upload.
* The execution succeeds, and the success count matches the number of rows.
* A profile from the file shows the mapped properties, in the compartment you expected.
* Properties you did not map are unchanged on an existing profile.
## Related pages
---
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