Cognite Data Fusion Fundamentals

Your CDF journey starts here. Get onboard!

Learn about Cognite Data Fusion - how to use it, its building blocks, and the value it brings to industrial organizations. CDF has proved to be a game-changer in industrial software innovation. It's an industrial DataOps product that contextually enriches data from different sources, providing a unified data model for easy access by humans and machines.

This is an introductory-level learning path for anyone new to CDF. The path consists of 9 courses and an assessment, and takes about 8 hours to go through. Passing the assessment earns you a badge and a certificate to display on Cognite Hub and LinkedIn. Upon completion, you'll be ready to start learning the different ways of using CDF that come with your specific role.

The path has two parts:

Concepts (Part 1)	Hands-on (Part 2)
This first part walks you through the architecture of CDF.	The second part guides you through using CDF to solve a simple use case.

Click the buttons below for more information.

Explain the value of CDF and its building blocks.
Use CDF to solve a simple use case.

There are no specific knowledge prerequisites.
For the hands-on part, we recommend using two monitors. This way, you can have the course and Cognite Data Fusion both open at the same time.

After passing the final assessment, you’ll gain a certificate. On Cognite Hub, you’ll be awarded the Onboarding badge.

Course	Learning goals
Cognite Data Fusion Architecture and Implementation Fundamentals	Explain what Cognite Data Fusion is. Describe the building blocks of CDF and how data flows between them. Discuss the main steps of implementing CDF.
Integration Fundamentals	Summarize the data’s journey from source systems to the staging area. Explain why it is important to write data to RAW first. Explain why we use transformations. Describe tools you can use to extract and transform data.
CDF Data Model Fundamentals	Explain Cognite’s data model. Describe the Cognite Data Fusion resource types to store and organize data. Identify resource types in your own organization.
Contextualization Fundamentals	Explain why contextualization is key to making data understandable. Summarize when each type of contextualization is most applicable. Compare the different types of contextualization.
Build and Consume Fundamentals	Articulate the advantages of using Cognite Charts. Discuss the connectors Cognite Data Fusion offers. Describe the InField, BestDay, Maintain, and Discover applications’ main uses.
Get Ready for Working with CDF!	Describe the use case you will be solving in CDF. Explain the prerequisites for completing the hands-on part of the Cognite Data Fundamentals learning path. Reach out to peers and instructors if you need help. Sign to CDF. Create a data set in CDF.
Working With CDF: Integrate	Upload a CSV file to RAW. Transform data from RAW into CDF resource types using transformations. Update data by rerunning the transformation. Document your dataset.
Working With CDF: Contextualize	Contextualize assets and events using Transformations. Contextualize assets and time series using Entity Matcher. Create interactive engineering diagram (contextualize P&IDs).
Working With CDF: Consume	Create a chart in Cognite Charts using contextualized data in CDF. Create a calculation in Cognite Charts.
Cognite Data Fusion Fundamentals Assessment	This assessment covers 9 courses that are included in the Cognite Data Fusion Fundamentals learning path. The questions challenge your basic understanding of Cognite Data Fusion (CDF). Earn a badge and certificate upon completion.

Connect with other learners and the rest of Cognite's Community on Cognite Hub.