Integrating Google BigQuery and Survicate allows you to collect and automatically send survey responses directly to your BigQuery data warehouse to store, query, and analyze user insights.
By integrating Survicate with BigQuery, you can:
Gain in-depth insights: Uncover patterns, identify trends, and get actionable insights from your survey data. For example, you can evaluate the effectiveness of your marketing campaigns by marrying survey responses with campaign performance data.
Simplify data management: Survicate structures and formats survey data automatically, making it ready for immediate use in BigQuery. The integration saves your time and effort in data preparation and lets you focus on more important tasks, like prioritizing feature requests by consolidating and analyzing the feedback received from your users.
Access real-time data: Your survey data is kept synced in real-time, so you have up-to-date insights for timely analysis and decision-making. With real-time data access, you can dynamically create targeted customer segments based on the most recent survey responses and other relevant data.
Benefit from improved security and efficiency: As a native integration, it ensures a fast connection, robust security, and guarantees no missed survey responses. Better efficiency means you can run thorough market research and competitive analysis by integrating survey responses with market trends and competitor insights.
In this article, you'll learn:
How Survicate & BigQuery Work Together
Survicate collects and sends survey data directly to your BigQuery data warehouse. This data includes all responses to your surveys, respondent details, and other metadata, which can then be analyzed using BigQuery's powerful SQL-like queries.
Setting Up Survicate & BigQuery Integration
To store your Survicate data in BigQuery, complete the following steps:
Create a project and enable BigQuery
Create a service account for Survicate
Connect BigQuery integration in Survicate
Step 1. Create a Project and Enable BigQuery *
To create a project and enable BigQuery:
Navigate to the Google Developers Console.
Configure the Google Cloud Platform
If you don’t have a project already, create one.
If you have an existing project, enable the BigQuery API. Once you’ve done so, you should see BigQuery in the “Resources” section of Cloud Platform.
3. Copy the project ID. You’ll need it when connecting BigQuery in the Survicate panel.
When you create your project, you must enable billing so Survicate can successfully write data.
* if you don't have it yet
Step 2. Create a service account for Survicate
To create a service account for Survicate:
From the Navigation panel on the left, select IAM & admin > Service accounts.
Click Create Service Account.
Enter a name for the service account (for example,
survicate-warehouse) and click Create.
Assign the service account the following roles:
BigQuery Data Owner(You would need to create a new dataset named “survicate” in case you want to add BigQuery Data Owner permission only to a single dataset.)
BigQuery Job User
Create a JSON key. The downloaded file will be used to connect the integration in the Survicate panel.
If you have trouble creating a new service account, refer to Google Cloud’s documentation about service accounts for more information.
Step 3. Connecting BigQuery in Survicate
Here's how to connect BigQuery in Survicate.
Find the Google BigQuery on the Integrations list, click Configure
Fill out two required fields: Project ID, Credentials
💡 Here's where to find the project ID in Google BigQuery
Follow the above instructions to create a dedicated project for Survicate data. Here's where you can find it in Google BigQuery:
Follow the above instructions to generate a dedicated .json file with credentials. Here's how the file looks after the download: