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Analyze Harvest time tracking data in Google Cloud BigQuery (REST) for enhanced reporting and insights. Latenode's visual editor and JavaScript nodes allow custom data transformations, plus affordable scaling for growing data needs.
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Create a New Scenario to Connect Harvest and Google Cloud BigQuery (REST)
In the workspace, click the โCreate New Scenarioโ button.
Add the First Step
Add the first node โ a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Harvest, triggered by another scenario, or executed manually (for testing purposes). In most cases, Harvest or Google Cloud BigQuery (REST) will be your first step. To do this, click "Choose an app," find Harvest or Google Cloud BigQuery (REST), and select the appropriate trigger to start the scenario.
Add the Harvest Node
Select the Harvest node from the app selection panel on the right.
Harvest
Add the Google Cloud BigQuery (REST) Node
Next, click the plus (+) icon on the Harvest node, select Google Cloud BigQuery (REST) from the list of available apps, and choose the action you need from the list of nodes within Google Cloud BigQuery (REST).
Harvest
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Google Cloud BigQuery (REST)
Authenticate Google Cloud BigQuery (REST)
Now, click the Google Cloud BigQuery (REST) node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud BigQuery (REST) settings. Authentication allows you to use Google Cloud BigQuery (REST) through Latenode.
Configure the Harvest and Google Cloud BigQuery (REST) 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 Harvest and Google Cloud BigQuery (REST) Integration
Use various Latenode nodes to transform data and enhance your integration:
JavaScript
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AI Anthropic Claude 3
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Google Cloud BigQuery (REST)
Trigger on Webhook
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Harvest
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Harvest, Google Cloud BigQuery (REST), and any additional nodes, donโt 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 โRun onceโ and triggering an event to check if the Harvest and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Harvest and Google Cloud BigQuery (REST) (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Harvest + Google Sheets + Slack: When a new time entry is created in Harvest, the data is added to a Google Sheet. Then, a summary of the new time entry is sent to a Slack channel.
Harvest + Google Sheets + Slack: When a timer is stopped in Harvest, the time entry is saved to a Google Sheet. A summary message with total billable hours is then posted to a Slack channel.
About Harvest
Automate time tracking with Harvest in Latenode. Sync time entries to accounting, payroll, or project management. Create flows that auto-generate invoices or trigger alerts for budget overruns. Latenode provides the flexibility to connect Harvest data to other apps and add custom logic, avoiding manual updates and delays.
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About Google Cloud BigQuery (REST)
Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.
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How can I connect my Harvest account to Google Cloud BigQuery (REST) using Latenode?
To connect your Harvest account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
Can I centralize Harvest time tracking data in BigQuery?
Yes, you can! Latenode simplifies data warehousing, enabling seamless transfer of Harvest data into Google Cloud BigQuery (REST) for analysis and reporting, all without complex coding.
What types of tasks can I perform by integrating Harvest with Google Cloud BigQuery (REST)?
Integrating Harvest with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
How does Latenode handle Harvest data security?
Latenode employs encryption and secure authentication to protect your Harvest data during transfer and storage. Access control is granular.
Are there any limitations to the Harvest and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: