Using Azure Services with Cognite Data Fusion for Low-Code/No-Code Applications [Cognite Official]

Introduction

Azure services like Power Automate and Logic Apps enable organizations to create automated workflows with minimal coding effort. By leveraging Cognite Data Fusion (CDF) APIs within these platforms, users can integrate and streamline their industrial data workflows effectively.

This presentation outlines the steps to build such workflows using Power Automate and similar approaches with Logic Apps, focusing on the integration with CDF.

Why Use Power Automate/Logic Apps with CDF?

• Low-Code/No-Code Development: Simplifies the process of building applications by using drag-and-drop features and pre-built templates.
• Automation: Streamlines repetitive tasks like data fetching, processing, and reporting.
• Seamless API Integration: Easily consume Cognite Data Fusion APIs to unlock and leverage contextualized data.
• Scalability: Enables workflows to scale with your operational needs using Azure's robust infrastructure.

Workflow Overview

Here’s how to create a workflow using Power Automate and Cognite Data Fusion APIs:

1. Set Up a Trigger

• Begin by selecting a trigger to initiate the workflow, such as a recurrence trigger (e.g., every 3 minutes) or an event-based trigger.

2. Generate Access Token

• Use the HTTP action to make a POST request to the Azure Active Directory token API to fetch an access token for Cognite Data Fusion. This step uses client credentials for authentication.

3. Parse the Token

• Use the Parse JSON action to extract the access_token from the token API's JSON response.

4. Store the Token

• Save the extracted token in a variable for reuse in subsequent API calls.

5: Make API Calls to CDF

• Add another HTTP action to interact with Cognite Data Fusion:
  • Method: GET or POST (depending on the API).
  • URI: E.g., https://api.cognitedata.com/api/v1/projects/{project}/assets.
  • Headers: Authorization: Bearer <token_variable>.
  • Body: Include any required parameters for the API call.

(below example calling RAW Dbs API, same way you can call your own CDF APIs)

Visual Workflow Example

Applications and Use Cases

• Automated Data Retrieval: Fetch timeseries, asset hierarchies, or data models on a schedule.
• Data Enrichment: Automatically contextualize raw data with CDF before passing it to other systems.
• Alerting and Notifications: Combine data from CDF with Microsoft Teams or email for real-time notifications.
• Workflow Triggering: Automatically trigger actions (e.g., maintenance work orders) based on CDF data.

Advantages

• Efficiency: Automates repetitive tasks, saving time and resources.
• Flexibility: Works with a variety of Azure triggers and connectors.
• Ease of Use: Requires minimal technical expertise to build robust workflows.
• Scalable: Supports workflows of varying complexity, from simple tasks to enterprise-grade solutions.