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# Parquet (Azure) connector

> Connect Mammoth to Parquet files in Azure Data Lake Storage with an access key, then query a file or folder and save it as a dataset.

The Parquet connector reads Parquet files stored in **Azure Data Lake Storage** and imports them into Mammoth as datasets. The connection form is titled "Azure Data Lake Storage Credentials." This connector is for Parquet-format files on Azure—use the [Google Cloud Storage connector](https://docs.mammoth.io/learn/connectors/google-cloud-storage-connector/) for Parquet files on GCS.

## Before you start

You need:

- An Azure storage account containing Parquet files
- Your storage account's **Access Key** (found in Azure Portal → Storage Account → Security + networking → Access keys)
- The **Account** name and **Container (File System)** name where your Parquet files are stored

## Step 1: Select the Parquet connector

1. In Mammoth, go to **Data Library** and click **+ New Dataset**
2. Select **Connectors**
3. Search for **Parquet**
4. Click the **Parquet** tile

## Step 2: Create a connection

Click **New Connection** to open the credential form.

![Parquet New Connection form titled Azure Data Lake Storage Credentials with Access Key, Account, and Container fields](https://docs.mammoth.io/api/v1/images/20260615_112514_Screenshot2026-05-221750231.jpg)

| Field | Description | Example |
| --- | --- | --- |
| **Access Key** | Azure Storage account access key (Key 1 or Key 2) | `abc123...` (long string) |
| **Account** | Azure storage account name | `mydatalake` |
| **Container (File System)** | Blob container name where your Parquet files are stored | `analytics-data` |

### Find your Azure access key

1. Open [Azure Portal](https://portal.azure.com) and go to your storage account
2. Under **Security + networking**, select **Access keys**
3. Copy **key1** (or key2)

After filling in the fields, click **Connect**. Mammoth validates the credentials and saves the connection; if validation fails, the error message appears at the bottom of the form.

## Step 3: Select a Parquet file and query your data

After connecting, select the connection under **Existing Connections**. Mammoth lists the folders (directory paths) in your container as **Profile** entries. Select one to browse the Parquet files within it in the **List of tables** panel, then click a file or directory to load a preview.

The **Enter SQL query** editor lets you write SQL against the selected data:

```sql
SELECT customer_id, event_type, event_date, revenue
FROM my_parquet_schema
WHERE event_date >= '2024-01-01'
```

![Parquet New Dataset dialog with file list, SELECT query, data preview, Save table as, and Save as dataset button](https://docs.mammoth.io/api/v1/images/20260615_112533_Screenshot2026-05-221723501.jpg)

See [Understanding data preview & query](https://docs.mammoth.io/learn/connectors/understanding-data-preview-query/) for a full guide.

## Step 4: Save the Parquet dataset

1. Enter a **dataset name** in the **Save table as** field
2. Check the **Update Method** (the default is **Replace all data**). To change it, click the edit icon, pick an option, and click **Save changes**:
   - **Replace all data**—Replaces all existing data
   - **Add new data**—Adds new data based on a unique sequential column
   - **Replace with new data**—Replaces existing data with new data based on a unique sequential column
   For **Add new data** and **Replace with new data**, also choose a **Key column**—a numeric or date column with incrementing values, such as an ID or a date.
3. Click **Save as dataset**. When the dataset is saved, click **Done**

## Troubleshoot Parquet connections

### Authentication fails

- Double-check the access key—it's a long base64 string; a single character error will fail
- Confirm the account name matches exactly (case-sensitive)

### Container not found

- The container name is case-sensitive in Azure
- Confirm the container exists in the Azure Portal under **Containers**

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Source: https://docs.mammoth.io/learn/connectors/parquet-connector.md · Updated: 2026-10-13