How to connect Google Cloud BigQuery and Wrike
Create a New Scenario to Connect Google Cloud BigQuery and Wrike
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 Wrike will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Wrike, 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 Wrike Node
Next, click the plus (+) icon on the Google Cloud BigQuery node, select Wrike from the list of available apps, and choose the action you need from the list of nodes within Wrike.

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Authenticate Wrike
Now, click the Wrike node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Wrike settings. Authentication allows you to use Wrike through Latenode.
Configure the Google Cloud BigQuery and Wrike 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 Wrike 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.

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AI Anthropic Claude 3
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Wrike
Trigger on Webhook
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Google Cloud BigQuery
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud BigQuery, Wrike, 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 Wrike integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Wrike (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 Wrike
Wrike + Google Sheets + Slack: When a new task is created in Wrike, its details are added to a Google Sheet. If the task deadline is within a week, a Slack message is sent to a designated channel to alert project managers.
Wrike + Google Cloud BigQuery + Google Sheets: Analyze Wrike task completion data by loading it into BigQuery. Use Google Sheets to visualize key metrics obtained from the BigQuery analysis, such as task completion rates and average completion times.
Google Cloud BigQuery and Wrike 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.
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About Wrike
Automate Wrike project updates and task assignments directly from other apps using Latenode. Sync data between Wrike and your CRM, database, or calendar. Create custom triggers based on project status changes and automate reporting. Latenode provides flexible integration with no-code tools or custom JavaScript, allowing you to tailor Wrike workflows without step limits.
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FAQ Google Cloud BigQuery and Wrike
How can I connect my Google Cloud BigQuery account to Wrike using Latenode?
To connect your Google Cloud BigQuery account to Wrike 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 Wrike accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate report generation based on BigQuery data in Wrike?
Yes, you can! Latenode enables automated reports by connecting BigQuery data to Wrike tasks, streamlining project updates with custom insights. Use no-code or JavaScript.
What types of tasks can I perform by integrating Google Cloud BigQuery with Wrike?
Integrating Google Cloud BigQuery with Wrike allows you to perform various tasks, including:
- Automatically create Wrike tasks from new BigQuery data entries.
- Update Wrike task statuses based on BigQuery data analysis results.
- Generate Wrike reports using data extracted from Google Cloud BigQuery.
- Trigger project updates in Wrike based on BigQuery data thresholds.
- Synchronize project-related metrics between Google Cloud BigQuery and Wrike.
How secure is my data when using the Google Cloud BigQuery integration?
Latenode employs robust encryption and secure authentication protocols, ensuring your data remains safe while connecting BigQuery to Wrike workflows.
Are there any limitations to the Google Cloud BigQuery and Wrike integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data synchronization may take time, depending on dataset size.
- Complex data transformations might require JavaScript knowledge.
- Rate limits imposed by Google Cloud BigQuery and Wrike still apply.