How to connect LinkedIn Data Scraper and Atera
Create a New Scenario to Connect LinkedIn Data Scraper and Atera
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 LinkedIn Data Scraper, triggered by another scenario, or executed manually (for testing purposes). In most cases, LinkedIn Data Scraper or Atera will be your first step. To do this, click "Choose an app," find LinkedIn Data Scraper or Atera, and select the appropriate trigger to start the scenario.

Add the LinkedIn Data Scraper Node
Select the LinkedIn Data Scraper node from the app selection panel on the right.

LinkedIn Data Scraper
Configure the LinkedIn Data Scraper
Click on the LinkedIn Data Scraper node to configure it. You can modify the LinkedIn Data Scraper URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Atera Node
Next, click the plus (+) icon on the LinkedIn Data Scraper node, select Atera from the list of available apps, and choose the action you need from the list of nodes within Atera.

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Atera

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

JavaScript
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AI Anthropic Claude 3
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Atera
Trigger on Webhook
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LinkedIn Data Scraper
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Iterator
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Webhook response

Save and Activate the Scenario
After configuring LinkedIn Data Scraper, Atera, 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 LinkedIn Data Scraper and Atera integration works as expected. Depending on your setup, data should flow between LinkedIn Data Scraper and Atera (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect LinkedIn Data Scraper and Atera
LinkedIn Data Scraper + Atera + Slack: When a new profile is found on LinkedIn Data Scraper based on specific search criteria, a new contact is created in Atera and a notification is sent to a Slack channel.
Atera + LinkedIn Data Scraper + HubSpot: When a new customer is created in Atera, find their LinkedIn company page using LinkedIn Data Scraper, and update the company information in HubSpot.
LinkedIn Data Scraper and Atera integration alternatives
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.
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About Atera
Use Atera with Latenode to automate IT support tasks. Trigger workflows on alerts, automatically create tickets, or update asset info. Integrate Atera's monitoring data with other apps for deeper insights and faster issue resolution. Customize rules and actions using Latenode's visual editor or JavaScript for precise automation.
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FAQ LinkedIn Data Scraper and Atera
How can I connect my LinkedIn Data Scraper account to Atera using Latenode?
To connect your LinkedIn Data Scraper account to Atera on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select LinkedIn Data Scraper and click on "Connect".
- Authenticate your LinkedIn Data Scraper and Atera accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically create Atera tickets from LinkedIn leads?
Yes, you can! Latenode's visual editor makes it easy to automate Atera ticket creation from scraped LinkedIn leads. Streamline lead management and ensure prompt follow-up with prospects.
What types of tasks can I perform by integrating LinkedIn Data Scraper with Atera?
Integrating LinkedIn Data Scraper with Atera allows you to perform various tasks, including:
- Automatically create Atera tickets from new LinkedIn Data Scraper leads.
- Enrich Atera contact data with up-to-date LinkedIn profiles.
- Trigger Atera service requests based on LinkedIn Data Scraper data insights.
- Sync scraped LinkedIn company data with Atera customer information.
- Update Atera asset details using LinkedIn Data Scraper profile information.
How to handle scraped LinkedIn profile data in Latenode?
Latenode provides flexible data transformation and routing. Use JavaScript or AI to process, filter, and map LinkedIn Data Scraper data.
Are there any limitations to the LinkedIn Data Scraper and Atera integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits of both LinkedIn Data Scraper and Atera APIs apply.
- Complex data transformations may require JavaScript knowledge.
- Initial setup requires understanding of both platforms' data structures.