This quarter’s release features new training on building industrial AI agents, enhancing 3D environments, improving data workflows and an all new and improved CDF fundamentals course to help you make better decisions and get more value from your data.

Courses: Build In-Depth Skills, Step-by-Step

Cognite Data Fundamentals with Data Modeling
A new and improved CDF Fundamentals course is now available. This introductory learning path is perfect for anyone new to Cognite Data Fusion. The updated content now covers the Core Data Model, hands-on exercises with Industrial Canvas, and an overview of Atlas AI. Complete the course to earn a shareable badge and certificate.

3D Configuration and Management
This course is designed to give you the skills to set up and configure 3D environments and integrate them into your daily work. You will learn to use 3D solutions to improve visualization, enhance decision-making, and boost operational efficiency.
This course is for anyone interested in learning about 3D technology and applying it in their professional field.

Microlearning videos: Bite-Sized Learnings

AI Agents in Industrial Workflows
Discover how Cognite's industrial AI agents, powered by Atlas AI, can help your teams act faster and with greater confidence. Learn how to leverage contextualized industrial data to streamline troubleshooting, automate routine tasks, and enhance operational efficiency.

Building Agents in Atlas AI
Master the process of building and customizing industrial AI agents using Cognite Atlas AI. This low-code workbench enables you to automate complex tasks by connecting to contextualized data in Cognite Data Fusion. See how to create, configure, and deploy agents to analyze time series, retrieve documents, and support decision-making—all without writing a single line of code.

Contextualizing Data for AI
Understand how to transform raw industrial data into a scalable, connected foundation for advanced workflows. Learn to build and enrich a Knowledge Graph using tools like Data Workflows, diagram parsing, and document parsing, enabling seamless reuse of data and powering robust AI agents and applications.

How-To Guide articles: Practical Tips from the Experts

Choosing the Right Extractor for Your CDF Integration
Cognite Data Fusion offers a wide range of extractors to integrate data from industrial and IT systems into a unified platform. These are divided into two main types: Prebuilt Extractors, installed within customer infrastructure to connect with systems like OSI PI, OPC UA, databases, SAP, and document libraries; and CDF-Hosted Scalable Extractors, managed in the cloud for high-volume, real-time data ingestion from sources such as Azure Event Hub, MQTT, Kafka, and RESTful APIs.

Understanding Function Memory Quotas in CDF
Learn best practices to prevent memory errors in CDF functions by designing workloads with memory limits in mind. This guide explains why breaking tasks into smaller, manageable chunks is the most effective approach.

How-To: Simple Streamlit App for CRUD Operations on CDF Data Model view
This guide shows you how to create a simple Streamlit web app to manage data model instances in Cognite Data Fusion (CDF) using the Python SDK. Learn to create, read, update, and delete (CRUD) instances in real time—perfect for demos, quick data manipulation, or onboarding users to structured data modeling.

Getting started with CDF performance testing 
This guide explains the importance of performance testing in Cognite Data Fusion (CDF) and how to assess key metrics like data ingestion rates, query performance, and API response times. It includes example notebooks to help you test efficiently, optimize costs, and ensure production readiness.

Changing Your Identity Provider (IdP): Playbook and Key Information 
This guide explains the relationship between projects, organizations, and Identity Providers (IdPs) in Cognite Data Fusion. It covers the implications of changing an organization’s IdP, including session invalidation, user ID reassignment, and potential data access issues, and provides guidance on planning and requesting IdP changes safely.

Unsubscribing from Cognite Charts Alerts
This guide explains how users can unsubscribe from Cognite Charts alerts and notifications, ensuring they no longer receive emails when time series thresholds are breached.

Fixing Video Playback Failure – Error Code: 101102
This guide helps troubleshoot Error Code 101102 when a training video fails to load. It covers common causes—like network restrictions, browser extensions, VPNs, or outdated browsers—and provides step-by-step solutions to restore smooth video playback.

Optimizing Data Ingestion Performance
Learn best practices to improve data ingestion performance in Cognite Data Fusion, including batching datasets, using progress monitoring, efficiently handling asset hierarchies, leveraging delta loads with the is_new function, and scheduling transformations for faster, more reliable workflows.

Product Updates: What's New to Enhance Your Workflow

Improving Cognite Functions stability with new rate limits
We're implementing new rate limits for Cognite Function calls to improve system performance and stability. A new limit of 250 concurrent running calls per CDF project will apply immediately to new projects and will go into effect on November 1, 2025, for existing projects. This change will affect a small number of projects with very high usage, ensuring a more equitable distribution of resources.

Power BI REST Connector now Generally Available
The Power BI REST API connector is now Generally Available (GA), offering better performance and broader capabilities than the legacy OData connector, which will be retired on August 18, 2026. The new REST API connector provides broader authentication support, enhanced data access, and a significant performance boost of up to 10x, and should be used for all new reports

New features for Cognite's GAP Connector
We've added two new capabilities to the GAP connector that address common challenges Petroleum Engineers face when working with GAP simulation models in production environments.

• Information Model Extraction The GAP connector can now automatically extract detailed flowsheet information models from simulator model revisions. This makes flowsheet data, including equipment, properties, and connections, accessible for analysis directly in CDF, eliminating the need for separate simulator access.
• External Dependencies Support This new feature allows you to manage simulation models by linking separate CDF files for components like well models or VLP tables, instead of repackaging the entire model. This simplifies updates, reduces storage overhead, and enables different team members to work on components independently.