> For the complete documentation index, see [llms.txt](https://docs.telm.ai/telmai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.telm.ai/telmai/connect-to-data.md).

# Connect to Data

## Create a Connection

Telmai provides a wide range of connectors, all of which can be found [here](https://www.telm.ai/integrations/). Some of the connectors are readily available in each tenant (see the list below), while the others can be enabled by contacting Telmai support.

To connect to your data source:

1. Navigate to Connections page using the left-side menu

<p align="center"><img src="/files/rdf1RTuxDGRcoOFLTEuh" alt=""><br></p>

2. Select desired scope:
   1. Global scope: Connection can be reused for any project
   2. Project scope: Connection can only be used for associated project
3. Click **+Add Connection** button
4. You will be prompted to specify the connector type and fill the details

<figure><img src="/files/r5OZ8CQljvnMFtlZ7KOq" alt=""><figcaption><p>Create a connection</p></figcaption></figure>

{% hint style="info" %}
Once you have selected the connection type, you will be asked to fill information specified to your connection

Connection can be reused to connect multiple datasets, tables, etc.
{% endhint %}

## Connect to a data asset <a href="#list-of-connectors-enabled-by-default" id="list-of-connectors-enabled-by-default"></a>

Once a connection is available, you can navigate to "Asset" page, and add your connection. Data assets must belong to a project.

1. Navigate to **Asset** page
2. Select target project, and click **+Add** button
3. Select source type
4. Select a created connection from the dropdown menu
   * You can also create a connection by clicking **+New Connection** button
5. Fill the data asset details, and follow onscreen instructions

### List of available connectors <a href="#list-of-connectors-enabled-by-default" id="list-of-connectors-enabled-by-default"></a>

* Google Big Query
* Google Cloud Storage
* AWS S3
* AWS Redshift
* AWS Athena
* Azure Blob
* Databricks
* Snowflake
* Salesforce
* SAP Hana
* Apache Iceberg

Telmai allows you to read a variety of file formats for the data stored in cloud buckets:

* Comma Separated Values (CSV)
* Tab Separated Values (TSV)
* Parquet
* JSON
* Databricks Delta