In today’s data-driven landscape, the ability to swiftly transform insights into action is paramount for businesses aiming to maintain a competitive edge. Many corporations currently face the challenge of transforming data insights into action in real-time. Disconnected data and analytics from the action layer are the primary reason that hinders their ability to take data-driven actions promptly. Organizations must bridge these gaps to respond quickly to emerging issues and opportunities by converting insights into action.
The ServiceNow and Databricks partnership enables a seamless end-to-end integration between data insight generation and automated actions. The ServiceNow platform will integrate with Databricks, enabling insights and analytics from Databricks to automatically trigger AI Agents or workflows on the ServiceNow platform. This integration provides a direct and real-time connection between the insights and the action.
What are potential use cases that can be solved via this integration?
A ServiceNow and Databricks joint customer can leverage data insights from Databricks to help them make better decisions and automate the consequent AI Agent/ workflow execution needed. Exemplary use cases include:
- Predictive Maintenance: Using Databricks analytics to foresee equipment failures, triggering automated maintenance alerts and OT workflows within ServiceNow.
- Cost Optimization: Identify cost-saving opportunities through Databricks analytics, and activate ServiceNow workflows (e.g., SPM) to manage costs based on established data thresholds.
- Supply Chain Resilience: Analyze supply chain data to anticipate potential disruptions, such as sudden demand swings, and initiate ServiceNow workflows (e.g., Supplier Lifecycle Operations) to mitigate risks proactively.
- Fraud Investigation: Analyze the changes in the customer’s behaviour across channels on Databricks and trigger a fraud investigation using ServiceNow Customer Service Management if an anomaly is detected.
How does this integration work?
Approach: The architectural approach behind this integration involves several key steps – below describes the steps for addressing an alert trigger handled via Databricks and ServiceNow.
- Notification Setup: In Databricks, a notification is configured to be sent upon the triggering of an alert. This notification is sent as a REST POST to a specified endpoint via a webhook.
- Flow Creation in ServiceNow: On the ServiceNow side, a flow with a REST trigger is created to receive the notification from Databricks as an endpoint. This flow is responsible for creating an incident in ServiceNow.
- Task Management: Once the flow is triggered and an incident is created in ServiceNow, a post is sent back to Databricks to add a record (e.g. to a custom table created within Databricks)
- Advanced Work Assignment: In ServiceNow, an advanced work assignment is configured to assign the incident to an available human agent / aligned AI agent. A simple playbook is also created to illustrate the idea of taking action on the incident.
- Recommended Plan of Action via AI Agent: ServiceNow AI Agent also offers a recommended plan of action to resolve the incident based on similar cases and the knowledge article
What is the architectural design behind the integration?
