https://github.com/ajaxbarcelonacruyff/bigquery_cost

Visualize BigQuery Query Costs in Looker Studio
https://github.com/ajaxbarcelonacruyff/bigquery_cost

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Visualize BigQuery Query Costs in Looker Studio

• Host: GitHub
• URL: https://github.com/ajaxbarcelonacruyff/bigquery_cost
• Owner: ajaxbarcelonacruyff
• Created: 2024-12-24T02:50:36.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-12-24T03:02:07.000Z (11 months ago)
• Last Synced: 2025-02-22T05:25:51.635Z (9 months ago)
• Size: 10.7 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          

# Connecting Looker Studio to BigQuery Using a Custom Query

This document outlines the steps to connect Looker Studio to BigQuery and retrieve data using a custom query.

---

## Step 1: Prepare the Custom Query

1. **Write Your Query**

   - Prepare a SQL query in the BigQuery console or your preferred SQL editor.

   - Ensure the query retrieves the necessary fields and filters the data appropriately for your report.

   - Example query:

     ```sql

     SELECT 

         project_id,

         user_email,

         creation_date,

         charges_jpy,

         charges_usd,

         total_gb_billed

     FROM `..`

     WHERE creation_date BETWEEN @start_date AND @end_date

     ORDER BY creation_date;

     ```

2. **Test Your Query**

   - Run the query in BigQuery to verify the results are as expected.

---

## Step 2: Connect Looker Studio to BigQuery

1. **Log in to Looker Studio**

   - Open [Looker Studio](https://lookerstudio.google.com/) and log in with your account.

2. **Add a New Data Source**

   - Click "Create" > "Data Source."

   - Select "BigQuery" as the connector.

3. **Choose the Custom Query Option**

   - In the BigQuery connector, select "Custom Query."

   - Choose the project associated with your query.

4. **Enter Your Query**

   - Paste the SQL query into the custom query editor.

   - Replace parameters (e.g., `@start_date`, `@end_date`) with fixed values or enable Looker Studio's date range controls for dynamic filtering.

5. **Authenticate**

   - Authenticate your access to the BigQuery project and dataset if prompted.

6. **Verify Schema**

   - Ensure all fields (columns) in the query are correctly recognized.

   - Adjust field data types if necessary (e.g., `charges_jpy` as a currency, `creation_date` as a date).

---

## Step 3: Create a Report in Looker Studio

1. **Build the Report**

   - Use the connected data source to create a new report.

   - Add visualizations such as:

     - **Bar Charts:** Compare costs by user or project.

     - **Line Graphs:** Display costs over time.

     - **Pie Charts:** Show cost distribution by category.

2. **Add Filters and Controls**

   - Add date range filters to dynamically filter data by date.

   - Use dimension filters to focus on specific projects, users, or categories.

3. **Style the Report**

   - Customize the layout, colors, and fonts for better readability.

---

## Step 4: Share and Manage the Report

1. **Share the Report**

   - Click "Share" > "Enable link sharing" to generate a link.

   - Set access permissions based on your needs (e.g., specific users or public access).

2. **Maintain the Report**

   - Periodically review the custom query to ensure it aligns with reporting requirements.

   - Update the query if the underlying data schema changes.

---

By following these steps, you can effectively use a custom query to connect Looker Studio to BigQuery, enabling precise and dynamic reporting.