# How to connect to your metadata

Turbovault4dbt supports various platforms for your metadata storage. Learn how to properly connect it to turbovault4dbt here!

## Snowflake

### Prerequisites

For using Turbovault4dbt you have to ensure the following prerequisites: 
- Having all five metadata tables within the same schema
- Having a role that can access the database and the schema where the metadata is located in
- Having the credentials to a user that can access the above

### Parameters

To connect Turbovault4dbt with your Snowflake Account, you have to add the following 5 parameters to your config.ini: 

    [Snowflake]
    account_identifier = <your_snowflake_account>
    database = <your_database>
    warehouse = <your_warehouse>
    role = <your_role>
    meta_schema = <schema_of_metadata>
    credential_path = <absolute_path_of_credential_file>

- **account_identifier**: Specify your account identifier. Follow [these notes](https://docs.snowflake.com/en/user-guide/python-connector-api.html#label-account-format-info) for help.
- **database**: Name of the default database to use.
- **warehouse**: Name of the default warehouse to use.
- **role**: Name of the default role to use.
- **meta_schema**: Name of the schema inside the database that holds the five [metadata](metadata.md) tables. 
- **credential_path**: Absolute path to a .ini file that needs to look like this:

### 


    [main]
    SNOWFLAKE_USER_NAME = <your_user_name>
    SNOWFLAKE_PASSWORD = <your_password>


## BigQuery

### Prerequisites

- Enable the [Google BigQuery API](https://cloud.google.com/bigquery) for your BigQuery project
- [Create a Service Account](https://cloud.google.com/iam/docs/creating-managing-service-accounts) that has access to your BigQuery project
- [Create and download](https://cloud.google.com/iam/docs/creating-managing-service-account-keys) a JSON Account Key for your Service Account


To connect Turbovault4dbt with your Google BigQuery database, you have to add the following 3 parameters to your config.ini:

    [BigQuery]
    metadata_dataset = <your_dataset>
    project_id = <your_project>
    credential_path = <absolute_path_of_credential_file>

- **metadata_dataset**: Name of the dataset (aka schema) within the database that your credentials have access to.
- **project_id**: ID of the project within your organization that your credentials have access to.
- **credential_path**: The absolute path of the JSON file that holds the Account Key for your Service Account. Must include the actual file name.

## Excel

### Prerequisites

- Having the .xlsx file that holds the five metadata sheets available on your local machine

To connect Turbovault4dbt to a locally available Excel file, you have to add the following parameter to your config.ini:

    [Excel]
    excel_path = <absolute_path_of_credential_file>

- **excel_path**: The absolute path to your .xlsx file. Must include the actual file name.

## Google Sheets

### Prerequisites

- Enable the [Google Sheets API](https://console.cloud.google.com/flows/enableapi?apiid=sheets.googleapis.com) for your GCP Project
- [Authorize OAuth credentials](https://developers.google.com/sheets/api/quickstart/python#authorize_credentials_for_a_desktop_application) for the Google Sheet and save the downloaded JSON on your local machine
- Have a Google Sheet available that holds your metadata

To connect TurboVault4dbt to your Google Sheet, you have to add the following 2 parameters to your config.ini: 

    [Google Sheets]
    sheet_url = <url_to_google_sheet>
    gcp_oauth_credentials = <absolute_path_to_credentials>

- **sheet_url**: The URL of your Google share. Retrieve it by using "Share"->"Copy Link"
- **gcp_oauth_credentials**: The absolute path to the OAuth credential JSON file on your local machine. Must include the actual file name.