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How to connect Harvest and Google Cloud BigQuery
Create a New Scenario to Connect Harvest and Google Cloud BigQuery
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 Harvest, triggered by another scenario, or executed manually (for testing purposes). In most cases, Harvest or Google Cloud BigQuery will be your first step. To do this, click "Choose an app," find Harvest or Google Cloud BigQuery, 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.
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Add the Google Cloud BigQuery Node
Next, click the plus (+) icon on the Harvest node, select Google Cloud BigQuery from the list of available apps, and choose the action you need from the list of nodes within Google Cloud BigQuery.
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Authenticate Google Cloud BigQuery
Now, click the Google Cloud BigQuery 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 settings. Authentication allows you to use Google Cloud BigQuery through Latenode.
Configure the Harvest and Google Cloud BigQuery 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 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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Save and Activate the Scenario
After configuring Harvest, Google Cloud BigQuery, 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 Harvest and Google Cloud BigQuery integration works as expected. Depending on your setup, data should flow between Harvest and Google Cloud BigQuery (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Harvest and Google Cloud BigQuery
Harvest + Google BigQuery + Slack: When a new time entry is created in Harvest, the data is sent to Google BigQuery. If the time exceeds the allocated budget for the project (based on a query in BigQuery), a notification is sent to a Slack channel.
Harvest + Google BigQuery + Google Sheets: Time tracking data from Harvest is stored and analyzed in Google BigQuery. Weekly reports summarizing time entries, project progress, and team performance are then automatically generated in Google Sheets.
Harvest and Google Cloud BigQuery integration alternatives
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
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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See how Latenode works
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FAQ Harvest and Google Cloud BigQuery
How can I connect my Harvest account to Google Cloud BigQuery using Latenode?
To connect your Harvest account to Google Cloud BigQuery on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Harvest and click on "Connect".
- Authenticate your Harvest and Google Cloud BigQuery accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze Harvest time entries in BigQuery?
Yes, you can! Latenode allows you to automate the transfer of Harvest data to BigQuery. Use visual blocks or JavaScript for transformations, unlocking advanced reporting and insights you couldn't easily access before.
What types of tasks can I perform by integrating Harvest with Google Cloud BigQuery?
Integrating Harvest with Google Cloud BigQuery allows you to perform various tasks, including:
- Automatically backing up Harvest data to Google Cloud BigQuery.
- Creating custom reports on employee time usage and project profitability.
- Combining Harvest data with other business data in BigQuery for analysis.
- Generating alerts based on time entry patterns or budget overruns.
- Performing advanced forecasting using machine learning models.
How secure is my Harvest data when using Latenode?
Latenode employs industry-standard encryption and security practices to protect your data during transfer and storage, ensuring the confidentiality of your Harvest information.
Are there any limitations to the Harvest and Google Cloud BigQuery integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Historical data transfer may require initial manual configuration.
- Real-time data synchronization depends on Harvest API rate limits.
- Complex data transformations might require JavaScript knowledge.
