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  10. Option 1: Set up Big Query as Data Source for Product Catalog

Option 1: Set up Big Query as Data Source for Product Catalog

Description

Google BigQuery is a fully managed, serverless cloud data warehouse that enables fast querying of large datasets. It is cost-effective, scalable to petabytes, and designed to help organizations turn big data into actionable business insights.

Prerequisites

Before setting up the connector, ensure you have:

  • A Google Cloud Project with BigQuery enabled
  • A Google Cloud Service Account with the roles:
    • BigQuery User
    • BigQuery Data Editor
  • A Service Account Key (JSON format) for authentication

Getting Started

  1. Go to Datahash Studio and log in with your credentials.
  2. Navigate to the Warehouse category under the Sources list.
  3. Click on the BigQuery connector tile.

Step 1: Select Data Type

Choose the type of integration you want to perform. Datahash currently supports:

  • Offline Events
  • Store Sales
  • Google Leads
  • Local Product Inventory
  • Product Catalog
  • Meta CLO
  • Snapchat Leads
  • TikTok Leads
  • LinkedIn Leads

For this setup, select Product Catalog, provide a Source Name, and click Next.

Step 2: Choose Integration Mode

You can integrate using one of two methods:

Option A: Table Path

  1. Download the File Format template provided in Datahash to understand the required data structure.
  2. Provide the following credentials:
    • JSON Key: Google Cloud JSON key for authentication
    • Project ID: Your GCP Project ID
    • Dataset ID: The dataset container in BigQuery holding your tables
    • Table Name: The table within the dataset that contains your product catalog data
  3. Click Validate Credentials.
  4. If validation succeeds, click Finish to complete the setup.

Option B: Query Path

  1. Provide the following credentials:
    • JSON Key: Google Cloud JSON key for authentication
    • Project ID: Your GCP Project ID
    • Dataset ID: The dataset from which data will be queried
  2. (Note: Table Name is not required here, as the query itself defines the table.)
  3. Click Validate Credentials.
  4. On the Configure screen, enter the SQL Query that will extract your product catalog data.
  5. Click Preview Results (optional) to confirm the query output.
  6. If everything looks good, click Finish to complete the setup.

Locating Required Credentials

Service Account Credentials (JSON Key)

  1. Log in to Google Cloud Console.
  2. Navigate to IAM & Admin → Service Accounts.
  3. Select an existing service account or create a new one with the roles:
    • BigQuery User
    • BigQuery Data Editor
  4. Go to Keys → Add Key → Create New Key → JSON.
  5. Download the JSON key file.

Project ID

  1. Log in to Google Cloud Console.
  2. Select the relevant project.
  3. Copy the Project ID displayed next to the project name.

Dataset ID

  1. In Google Cloud Console, go to BigQuery → BigQuery Studio.
  2. Select your project and view the list of datasets.
  3. Click on the dataset to view its Dataset ID.

Table Name

  1. In BigQuery Studio, expand the dataset.
  2. Locate the required table name.
  3. Copy the Table Name and provide it in Datahash (only for Table Path).

Notes

  • If setup is exited before completion, the connector will remain in Pending status. You can resume setup anytime by clicking on the connection name.
  • The connection status will show as Completed once credentials and mappings are successfully validated.

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