How to connect Outscraper and Google Cloud BigQuery (REST)
Create a New Scenario to Connect Outscraper and Google Cloud BigQuery (REST)
In the workspace, click the βCreate New Scenarioβ button.

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

Add the Outscraper Node
Select the Outscraper node from the app selection panel on the right.

Outscraper
Configure the Outscraper
Click on the Outscraper node to configure it. You can modify the Outscraper URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Cloud BigQuery (REST) Node
Next, click the plus (+) icon on the Outscraper 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).

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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 Outscraper 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 Outscraper and Google Cloud BigQuery (REST) 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 donβt 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Outscraper, Google Cloud BigQuery (REST), and any additional nodes, donβt 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 βRun onceβ and triggering an event to check if the Outscraper and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Outscraper and Google Cloud BigQuery (REST) (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Outscraper and Google Cloud BigQuery (REST)
Outscraper + Google Cloud BigQuery (REST) + Google Sheets: Outscraper scrapes product data. BigQuery stores this data. Google Sheets visualizes the trends present in the BigQuery data.
Google Cloud BigQuery (REST) + Outscraper + Slack: When new data is added to BigQuery from Outscraper's task, a summary notification containing relevant information is sent to a Slack channel.
Outscraper and Google Cloud BigQuery (REST) integration alternatives
About Outscraper
Need to scrape web data at scale? Integrate Outscraper into Latenode to automate data extraction workflows. Get structured data from search engines, social media, and e-commerce sites without complex coding. Combine with Latenode's no-code tools, JS scripts, and webhooks for custom data pipelines that adapt to any business need.
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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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FAQ Outscraper and Google Cloud BigQuery (REST)
How can I connect my Outscraper account to Google Cloud BigQuery (REST) using Latenode?
To connect your Outscraper account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Outscraper and click on "Connect".
- Authenticate your Outscraper and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze scraped product data in BigQuery?
Yes, you can! Latenode lets you automate data transfer, enabling advanced analysis and reporting in BigQuery, enhancing business intelligence with minimal coding.
What types of tasks can I perform by integrating Outscraper with Google Cloud BigQuery (REST)?
Integrating Outscraper with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automating competitor price monitoring and analysis.
- Building lead generation databases with enriched business data.
- Analyzing market trends derived from web scraping.
- Creating custom reports from extracted data in BigQuery.
- Storing and analyzing social media sentiment data.
How does Latenode handle large Outscraper data volumes?
Latenode is built for scalability. It efficiently manages high data volumes from Outscraper, ensuring smooth BigQuery integration, leveraging its advanced architecture.
Are there any limitations to the Outscraper and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data schema setup in BigQuery is required.
- Rate limits of both Outscraper and BigQuery apply.
- Complex data transformations might require JavaScript knowledge.