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Analyze CloudTalk call data in Databricks for insights that boost agent performance and customer satisfaction. Latenode’s no-code visual editor simplifies setup, while affordable execution-based pricing maximizes your ROI when scaling call analytics.
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Create a New Scenario to Connect CloudTalk and Databricks
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 CloudTalk, triggered by another scenario, or executed manually (for testing purposes). In most cases, CloudTalk or Databricks will be your first step. To do this, click "Choose an app," find CloudTalk or Databricks, and select the appropriate trigger to start the scenario.
Add the CloudTalk Node
Select the CloudTalk node from the app selection panel on the right.
CloudTalk
Configure the CloudTalk
Click on the CloudTalk node to configure it. You can modify the CloudTalk URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Databricks Node
Next, click the plus (+) icon on the CloudTalk node, select Databricks from the list of available apps, and choose the action you need from the list of nodes within Databricks.
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Databricks
Authenticate Databricks
Now, click the Databricks node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Databricks settings. Authentication allows you to use Databricks through Latenode.
Configure the CloudTalk and Databricks 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 CloudTalk and Databricks 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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Databricks
Trigger on Webhook
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CloudTalk
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring CloudTalk, Databricks, 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 CloudTalk and Databricks integration works as expected. Depending on your setup, data should flow between CloudTalk and Databricks (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
CloudTalk + Databricks + Google Sheets: When a new call is recorded in CloudTalk, the call data is sent to Databricks. Databricks processes the data and queries the SQL Warehouse. The results are then summarized and added as a new row in Google Sheets for daily reports.
Databricks + CloudTalk + Slack: Databricks monitors call data using a scheduled job. When anomalies are detected via a query, Databricks triggers a job run which sends an alert to a specific CloudTalk user and posts details of the anomaly to a designated Slack channel.
About CloudTalk
Automate CloudTalk call and SMS data within Latenode. Trigger workflows on new calls, messages, or agent status changes. Update CRMs, send alerts, or generate reports automatically. Use Latenode's visual editor and data transformation tools to customize call center automations without complex coding, and scale your workflows efficiently.
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About Databricks
Use Databricks inside Latenode to automate data processing pipelines. Trigger Databricks jobs based on events, then route insights directly into your workflows for reporting or actions. Streamline big data tasks with visual flows, custom JavaScript, and Latenode's scalable execution engine.
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How can I connect my CloudTalk account to Databricks using Latenode?
To connect your CloudTalk account to Databricks on Latenode, follow these steps:
Can I analyze call sentiment from CloudTalk in Databricks?
Yes, you can! Latenode enables sentiment analysis of CloudTalk calls and stores results in Databricks. Use AI steps for advanced insights, boosting customer service and product feedback loops.
What types of tasks can I perform by integrating CloudTalk with Databricks?
Integrating CloudTalk with Databricks allows you to perform various tasks, including:
How do I automate CloudTalk call data backups on Latenode?
Use Latenode to schedule regular CloudTalk data exports and automatically save them in Databricks. This guarantees data safety and compliance with no code required.
Are there any limitations to the CloudTalk and Databricks integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: