Google Cloud BigQuery and LinkedIn Data Scraper Integration

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Enrich Google Cloud BigQuery datasets with LinkedIn Data Scraper insights, visualizing professional trends. Latenode’s low-code platform simplifies data transformation and ensures scalability, while keeping automation costs predictable.

Swap Apps

Google Cloud BigQuery

LinkedIn Data Scraper

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud BigQuery and LinkedIn Data Scraper

Create a New Scenario to Connect Google Cloud BigQuery and LinkedIn Data Scraper

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 LinkedIn Data Scraper will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or LinkedIn Data Scraper, 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.

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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.

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Add the LinkedIn Data Scraper Node

Next, click the plus (+) icon on the Google Cloud BigQuery node, select LinkedIn Data Scraper from the list of available apps, and choose the action you need from the list of nodes within LinkedIn Data Scraper.

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Authenticate LinkedIn Data Scraper

Now, click the LinkedIn Data Scraper node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your LinkedIn Data Scraper settings. Authentication allows you to use LinkedIn Data Scraper through Latenode.

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Configure the Google Cloud BigQuery and LinkedIn Data Scraper Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Set Up the Google Cloud BigQuery and LinkedIn Data Scraper 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 Google Cloud BigQuery, LinkedIn Data Scraper, 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 LinkedIn Data Scraper integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and LinkedIn Data Scraper (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 LinkedIn Data Scraper

LinkedIn Data Scraper + Google Sheets: Scrape LinkedIn profile data based on search criteria and add it to a Google Sheet for team review and analysis.

LinkedIn Data Scraper + Slack: When a new job is posted at a target company on LinkedIn (identified through scraping), send a notification to a dedicated Slack channel.

Google Cloud BigQuery and LinkedIn Data Scraper 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.

About LinkedIn Data Scraper

Need LinkedIn data for leads or market insights? Automate scraping profiles and company info inside Latenode workflows. Extract data, enrich it with AI, then push it to your CRM or database. Latenode's visual editor and affordable pricing make data-driven outreach scalable and cost-effective.

See how Latenode works

FAQ Google Cloud BigQuery and LinkedIn Data Scraper

How can I connect my Google Cloud BigQuery account to LinkedIn Data Scraper using Latenode?

To connect your Google Cloud BigQuery account to LinkedIn Data Scraper 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 LinkedIn Data Scraper accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I enrich BigQuery data with LinkedIn profile information?

Yes, you can! Latenode's visual editor makes it easy to map LinkedIn Data Scraper results directly into your Google Cloud BigQuery tables, automating data enrichment and analysis.

What types of tasks can I perform by integrating Google Cloud BigQuery with LinkedIn Data Scraper?

Integrating Google Cloud BigQuery with LinkedIn Data Scraper allows you to perform various tasks, including:

  • Automatically updating lead data in BigQuery with LinkedIn profile details.
  • Building comprehensive datasets for market research and competitive analysis.
  • Creating custom reports on industry trends based on LinkedIn data.
  • Analyzing employee skill sets across different companies.
  • Tracking career progression and network changes using historical data.

Can I schedule my Google Cloud BigQuery data extractions within Latenode?

Yes, Latenode lets you schedule extractions from Google Cloud BigQuery to run automatically, ensuring consistent data flow and analysis.

Are there any limitations to the Google Cloud BigQuery and LinkedIn Data Scraper integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • LinkedIn's rate limits may affect the frequency of data scraping.
  • BigQuery storage costs apply based on your data volume.
  • Complex data transformations might require JavaScript coding.

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