Overview
Integrating Triple Whale with BigQuery allows you to take your data analysis to the next level by seamlessly exporting data from Triple Whale to BigQuery through the workflows feature. This powerful, data-out integration empowers you to consolidate and analyze your Triple Whale data alongside other business data, uncovering deeper insights and enabling custom reporting.
With BigQuery’s advanced analytics capabilities, you can perform complex queries, track trends, and make data-driven decisions to refine your marketing strategy. By connecting Triple Whale to BigQuery, you gain the flexibility to explore your data in new ways, supporting a more robust and informed approach to business growth.
Get Connected
A brief walkthrough video of connecting BigQuery to Triple Whale.
To get started, head to Settings > Integrations. Locate BigQuery and click Connect.
You will be prompted for three items:
Project ID
Dataset ID
Permissions
Project ID
To locate the Project ID of the project you'd like to use, head to your Google Cloud Dashboard and use the dropdown at the top of the page to select the desired project. You will then see the Project ID located within the Project info section.
Note: To create a new project, head to BigQuery > Manage Resources and click Create Project.
Dataset ID
To locate the Dataset ID you'd like Triple Whale to export data into, head to BigQuery and open the desired project. The dataset name is its' ID - in the example shown below, sample_dataset_id.
Creating a new Dataset in BigQuery
To create a new dataset in BigQuery, click the ⋮ symbol next to your Project ID and click Create Dataset.
Permissions
Lastly, you will need to add Triple Whale as a BigQuery Data Editor for the desired dataset. To do so, click the ⋮ symbol next to your Dataset ID, select Share > Manage Permissions, and click Add Principal. In the New principals text field, input srv-big-query-exporter@shofifi.iam.gserviceaccount.com and for the role, select BigQuery Data Editor.
Once you have input the Project ID, Dataset ID, and checked the box confirming that permissions have been granted, click Save.
Using Workflows for Exporting Data to BigQuery
Triple Whale’s workflows enable seamless data export to BigQuery, allowing for in-depth analysis and custom reporting. Here’s how to set it up:
Select BigQuery as the Destination: In the final step of your Workflow setup, choose BigQuery as the export destination.
Configure Settings: Provide any necessary details for BigQuery integration, such as dataset and table names, to ensure data is properly routed.
Schedule and Run: Choose whether to run the Workflow on-demand or at scheduled intervals. Scheduling ensures data is consistently sent to BigQuery, keeping your insights fresh and up-to-date.
Practical Examples for Exporting Data to BigQuery
With BigQuery as your data destination, Workflows can automate advanced analytical tasks, such as:
Automated Performance Reporting: Export key performance metrics to BigQuery, where you can run advanced queries and maintain continuously updated reports for real-time insights.
Detailed Transaction Analysis: Sync transaction data with BigQuery to perform in-depth analyses of customer behavior, purchase trends, and revenue performance.
Comprehensive Marketing Attribution: Use BigQuery to combine data from multiple channels exported from Triple Whale, providing a unified view of your marketing attribution and allowing for more accurate ROI calculations.
Custom Data Models: With Triple Whale exporting data to BigQuery, you can build custom data models and dashboards tailored to your unique business metrics and analytical needs.
Conclusion
By leveraging Triple Whale’s workflows to export data to BigQuery, you gain the flexibility to conduct complex analyses, customize reports, and enhance your data-driven decision-making processes. This integration empowers you to turn raw data into actionable insights, supporting more strategic business growth.