Snowflake

Snowflake is a cloud-native data warehouse built for performance and scale. DataHawk uses Snowflake as the hosted database for users who work with Power BI, Excel, Tableau, or any SQL-compatible tool outside of Google's ecosystem.

Your DataHawk Snowflake database

When you set up a Snowflake destination, DataHawk creates and manages a dedicated database containing all your collected data. You don't need to configure or maintain anything. We handle setup, scaling, and maintenance.

What's included:

• Daily updated tables, fresh and analysis-ready
• Optimized views, cleaned and enriched by DataHawk
• No infrastructure management on your side

DataHawk refreshes your Snowflake database every day. Not all data arrives at the same time. Some datasets are populated later in the day depending on when Amazon's API makes them available. See the individual dataset pages in the Knowledge Hub for dataset-specific freshness details.

Option 1 — DataHawk-hosted Snowflake (recommended for most users)

This is the default setup. DataHawk creates and hosts the Snowflake database for you.

How to find your credentials

In your DataHawk workspace, navigate to Setup > Destinations > Snowflake > See Credentials.

Your credentials page will contain the following:

Keep these credentials safe. You'll use them to connect your database to your BI tool or SQL editor.

Option 2 — Self-hosted Snowflake (advanced)

If you already use Snowflake and prefer to have DataHawk write data into your own Snowflake account, this is possible.

To get started, contact your Account Manager and share your:

• Snowflake account identifier
• Cloud hosting provider (AWS, Azure, GCP) and region

Snowflake Credits

DataHawk-hosted Snowflake databases consume Snowflake credits. Credits are used when your warehouse is active (running queries).

Contact your DataHawk representative for details on how to track and manage your usage.

Query timeout (30 minutes)

How to verify the limit: In your SQL client, run SHOW PARAMETERS LIKE 'STATEMENT_TIMEOUT_IN_SECONDS' IN WAREHOUSE <your_warehouse>;: The value should be 1800 (seconds).

Write queries that finish in under 30 minutes:

• Filter early: Restrict by marketplace_key, date, brand, or ASIN before joining wide tables.
• Limit date ranges in exploratory queries (e.g. WHERE date >= DATEADD(month, -3, CURRENT_DATE)).
• Use the curated REPORTS.* views when possible. They are pre-aggregated and substantially faster than building from raw layers.
• Avoid SELECT * on the largest raw tables (advertising, profit ledger, search). Project only the columns you need.
• Break very large extracts into multiple smaller queries (e.g. month-by-month) rather than a single multi-year scan.

If a query is cancelled by the timeout:

• Check the Snowflake query history (QUERY_HISTORY) to confirm the cancellation reason.
• See Accessing our Snowflake database from behind a firewall for network-side issues that can also cause long-running or stalled queries.

Compatible tools

Snowflake connects natively to most modern data tools. Common examples:

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Where to go next

Power BI is the recommended tool for DataHawk users on Snowflake. DataHawk provides pre-built Power BI templates covering sales, advertising, keywords, profitability, and more.