How to connect Google Cloud BigQuery and Google Dialogflow ES
Create a New Scenario to Connect Google Cloud BigQuery and Google Dialogflow ES
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud BigQuery, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery or Google Dialogflow ES will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Google Dialogflow ES, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery Node
Select the Google Cloud BigQuery node from the app selection panel on the right.

Google Cloud BigQuery
Configure the Google Cloud BigQuery
Click on the Google Cloud BigQuery node to configure it. You can modify the Google Cloud BigQuery URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Dialogflow ES Node
Next, click the plus (+) icon on the Google Cloud BigQuery node, select Google Dialogflow ES from the list of available apps, and choose the action you need from the list of nodes within Google Dialogflow ES.

Google Cloud BigQuery
⚙
Google Dialogflow ES
Authenticate Google Dialogflow ES
Now, click the Google Dialogflow ES node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Dialogflow ES settings. Authentication allows you to use Google Dialogflow ES through Latenode.
Configure the Google Cloud BigQuery and Google Dialogflow ES Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud BigQuery and Google Dialogflow ES Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

JavaScript
⚙
AI Anthropic Claude 3
⚙
Google Dialogflow ES
Trigger on Webhook
⚙
Google Cloud BigQuery
⚙
⚙
Iterator
⚙
Webhook response
Save and Activate the Scenario
After configuring Google Cloud BigQuery, Google Dialogflow ES, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud BigQuery and Google Dialogflow ES integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Google Dialogflow ES (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud BigQuery and Google Dialogflow ES
Google Dialogflow ES + Google Sheets: When a user interacts with the Dialogflow ES chatbot, their intent is detected, and the relevant data (intent, user input, timestamp) is added as a new row in a Google Sheet. This allows for tracking chatbot usage and identifying trends in user queries.
Google Dialogflow ES + Slack: Monitor intent detections in Dialogflow. If a specific intent related to 'performance issues' is detected, a message is sent to a dedicated Slack channel to alert the team. The message includes details about the intent and when it happened.
Google Cloud BigQuery and Google Dialogflow ES integration alternatives
About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
Similar apps
Related categories
About Google Dialogflow ES
Use Google Dialogflow ES in Latenode to build smart chatbots and automate customer service tasks. Connect Dialogflow to your databases, CRMs, or other apps for personalized responses. Create visual workflows that handle complex conversations without code, adding custom logic with JavaScript where needed. Scale your AI-powered interactions using Latenode's flexible automation platform.
Similar apps
Related categories
See how Latenode works
FAQ Google Cloud BigQuery and Google Dialogflow ES
How can I connect my Google Cloud BigQuery account to Google Dialogflow ES using Latenode?
To connect your Google Cloud BigQuery account to Google Dialogflow ES on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery and click on "Connect".
- Authenticate your Google Cloud BigQuery and Google Dialogflow ES accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze chatbot conversation data using BigQuery?
Yes, you can! Latenode simplifies this by allowing seamless data transfer and analysis, providing valuable insights to optimize your Google Dialogflow ES chatbot performance.
What types of tasks can I perform by integrating Google Cloud BigQuery with Google Dialogflow ES?
Integrating Google Cloud BigQuery with Google Dialogflow ES allows you to perform various tasks, including:
- Store and analyze chatbot conversation history in BigQuery.
- Use BigQuery data to personalize chatbot responses dynamically.
- Trigger Dialogflow ES intents based on BigQuery data insights.
- Create dashboards to visualize chatbot performance metrics.
- Automate data exports from Dialogflow ES into BigQuery.
How secure is Google Cloud BigQuery data when using Latenode?
Latenode uses secure authentication and data encryption to ensure your Google Cloud BigQuery data remains protected during all integration processes.
Are there any limitations to the Google Cloud BigQuery and Google Dialogflow ES integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex BigQuery queries may require optimization for efficient data transfer.
- Large data volumes may impact workflow execution time.
- Real-time data synchronization depends on Google Cloud BigQuery API limits.