> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Set up a Snowflake data warehouse

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This tutorial walks you through setting up a test Snowflake data warehouse and connecting it to Anaconda Platform so you can query data from your workstations and Metaflow flows.

<Note>
  Creating a resource integration requires an administrator role. If you do not have administrator access, ask your administrator to create the integration before you begin.
</Note>

By the end of this tutorial, you will have:

* A Snowflake user, role, database, and schema configured for the platform
* A Snowflake integration registered on the platform
* A workstation notebook that reads data from Snowflake
* A Metaflow flow that queries Snowflake

## Set up Snowflake resources

Create a Snowflake user and role that can read and write to a database. You can use an existing user, role, and database if you have them. Otherwise, use the following template to create the minimal components:

<Accordion title="Minimal Snowflake setup SQL">
  ```sql theme={null}
  -- 1. Create a role
  CREATE ROLE IF NOT EXISTS <YOUR_ROLE>;

  -- 2. Create a user and set default DB/schema
  CREATE USER IF NOT EXISTS <YOUR_USER>
    PASSWORD = 'StrongPasswordHere1!'
    LOGIN_NAME = '<YOUR_USER>'
    MUST_CHANGE_PASSWORD = FALSE
    DEFAULT_ROLE = <YOUR_ROLE>
    DEFAULT_WAREHOUSE = <YOUR_WAREHOUSE>
    DEFAULT_NAMESPACE = <YOUR_DB>.<YOUR_SCHEMA>
    COMMENT = 'User for Demo';

  -- 3. Grant the role to the user
  GRANT ROLE <YOUR_ROLE> TO USER <YOUR_USER>;

  -- 4. Grant usage on a warehouse to the role
  GRANT USAGE ON WAREHOUSE <YOUR_WAREHOUSE> TO ROLE <YOUR_ROLE>;

  -- 5. Create a test database and schema for the user to read/write
  CREATE DATABASE IF NOT EXISTS <YOUR_DB> COMMENT = 'Database for Demo';
  CREATE SCHEMA IF NOT EXISTS <YOUR_DB>.<YOUR_SCHEMA> COMMENT = 'Schema for Demo';

  -- 6. Grant privileges on the new database/schema to the role
  GRANT ALL PRIVILEGES ON DATABASE <YOUR_DB> TO ROLE <YOUR_ROLE>;

  -- 7. Grant privileges on the schema
  GRANT ALL PRIVILEGES ON SCHEMA <YOUR_DB>.<YOUR_SCHEMA> TO ROLE <YOUR_ROLE>;

  -- (Optional) Grant privileges on future objects in the schema
  -- so that the role automatically gets read/write privileges
  -- for newly created tables or views
  GRANT ALL PRIVILEGES ON FUTURE TABLES IN SCHEMA <YOUR_DB>.<YOUR_SCHEMA> TO ROLE <YOUR_ROLE>;
  GRANT ALL PRIVILEGES ON FUTURE VIEWS IN SCHEMA <YOUR_DB>.<YOUR_SCHEMA> TO ROLE <YOUR_ROLE>;
  ```

  <Comments>
    Replace \<YOUR\_ROLE> with the name of the Snowflake role to create.<br />
    Replace \<YOUR\_USER> with the name of the Snowflake user to create.<br />
    Replace \<YOUR\_WAREHOUSE> with the name of the Snowflake warehouse the user runs queries on.<br />
    Replace \<YOUR\_DB> with the name of the database to create.<br />
    Replace \<YOUR\_SCHEMA> with the name of the schema to create.
  </Comments>
</Accordion>

## Register the Snowflake integration

1. Select **Integrations** in the left-hand navigation.
2. Click **Snowflake** in the **Add an Integration** section.
3. Enter a name for the integration.
4. Enter a description for the integration.
5. Enter your Snowflake credentials.
6. Click **Add**.

The integration panel includes a query to run on Snowflake to establish the security integration.

## Download the tutorial content

Download the tutorial content to your workstation:

```bash theme={null}
outerbounds tutorials pull --url https://outerbounds-journeys-content.s3.us-west-2.amazonaws.com/main/journeys.tar.gz --destination-dir ~/learn
```

The Snowflake tutorial content is in `~/learn/snowflake`. If you prefer a different location, replace `~/learn` with a directory of your choice.

<Tip>
  This command downloads all tutorial content as a single bundle. If you've already worked through other tutorials, you likely already have this and do not need to run the command again.
</Tip>

## Validate your setup

Open the notebook in `00-nb` from the `~/learn/snowflake` directory. Before running it, update the `integration`, `schema`, and `table_name` variables with your Snowflake integration name, schema, and table. This notebook validates that you can access Snowflake from an Anaconda Platform workstation.

## Query Snowflake from a notebook

The same notebook walks you through reading data from Snowflake after validation succeeds.

## Query Snowflake from a flow

Open the `01-flow` directory from the `~/learn/snowflake` directory. This directory contains a Metaflow flow that queries Snowflake. Before running it, update the `my_integration`, `my_schema`, and `my_table_name` variables in `flow.py` with the same values you used in the notebook.

Run the flow:

```bash theme={null}
cd ~/learn/snowflake/01-flow
python flow.py --environment=fast-bakery run --with kubernetes
```

## Next steps

To build on this tutorial:

* Query multiple tables and join data across schemas.
* Build automated reporting pipelines that read from Snowflake.
* Integrate Snowflake queries into your ML training workflows.