Integrations Databricks calltrackingmetrics
Databricks + calltrackingmetrics

Connect Databricks and calltrackingmetrics to Build Intelligent Automations

Choose a Trigger

Databricks

When this happens...

Choose an Action

calltrackingmetrics

Automatically do this!

Enable Integrations or automations with these events of Databricks and calltrackingmetrics

Enable Integrations or automations with these events of Databricks and calltrackingmetrics

Actions

Create Cluster

Create Cluster

Creates a new Databricks cluster for processing tasks.

Create a Directory

Create a Directory

Create a directory by a path.

Delete a Job

Delete a Job

This action deletes a job by ID.

Create a Repo

Create a Repo

Creates a repo in the workspace and links it to the remote Git repo specified.

Delete Repo

Delete Repo

Delete a Repo

Request a new Action for Databricks

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Frequently Asked Questions

How do I start an integration between Databricks and calltrackingmetrics?

To start, connect both your Databricks and calltrackingmetrics accounts to viaSocket. Once connected, you can set up a workflow where an event in Databricks triggers actions in calltrackingmetrics (or vice versa).

Can we customize how data from Databricks is recorded in calltrackingmetrics?

Absolutely. You can customize how Databricks data is recorded in calltrackingmetrics. This includes choosing which data fields go into which fields of calltrackingmetrics, setting up custom formats, and filtering out unwanted information.

How often does the data sync between Databricks and calltrackingmetrics?

The data sync between Databricks and calltrackingmetrics typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.

Can I filter or transform data before sending it from Databricks to calltrackingmetrics?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between Databricks and calltrackingmetrics?

Yes, you can set conditional logic to control the flow of data between Databricks and calltrackingmetrics. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.

Databricks

About Databricks

Databricks is a cloud-based data platform that provides a collaborative environment for data engineering, data science, and machine learning. It offers a unified analytics platform that simplifies data processing and enables organizations to build and deploy AI models at scale. With its powerful integration capabilities, Databricks allows teams to work together seamlessly, accelerating innovation and driving data-driven decision-making.

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calltrackingmetrics

About calltrackingmetrics

CallTrackingMetrics is the only digital platform that uses call tracking intelligence to inform contact center automation—resulting in a more personalized customer experience. Discover which marketing campaigns are generating leads and conversions, and use that data to automate call flows and power your contact center.

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