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Cognite Data Fusion Trial

Cognite Data Fusion Trial

Get hands-on with our applications, the SDKs, and APIs, and explore their features. Get your personal Cognite Data Fusion trial project!


Get your own trial project to explore Cognite Data Fusion (CDF).

Sign up for a Cognite Data Fusion Trial Project to get started.

About the trial project

Limited availability

The trial project is currently available only for Cognite employees.

The trial project is a personal project that you can use to explore CDF and its features. It is a fully functional CDF project with the following restrictions:

  • Sign in with your Google account. Both enterprise and personal accounts work.
  • It is only for your personal use.
  • Do not load/ingest sensitive or confidential data into the project.
  • Protect the credentials you receive by email, and do not share them with others.
  • There are no Service Level Agreements for trial projects.
  • The trial project may be deleted if inactive for an extended period.

Get started

After signing up, you will receive an email with your project name, a client id, and a client secret you can use to access the data in your project from the CDF SDKs and APIs. However, when you have signed up, you can go directly to and sign in with your Google account.

A good starting point is to load some data into your project as part of the Data Modeling Quickstart. In the email you received, you will have an IDP_CLIENT_ID and IDP_CLIENT_SECRET that you will use in the quickstart to load data into your project.

Install Python

Install Python to use the cookiecutter tool and the data model examples. Once the installation is complete, the requirements.txt file allows you to install the required packages.


To download and install Python, see Download Python. We recommend Python v3.11. The data model examples and tools have been tested with Python 3.10 and 3.11.

Note: If you prefer poetry as a package manager, there is a toml file for poetry package manager. Poetry requires Python 3.11. If you don't have a preference, use the requirements.txt file and pip install as described above.

Load data

If you want to load data, take the project name, client id, and secret from the email you received and use the following commands to load data into your project. Make sure to Install Python before you get started:

pip install cookiecutter

Fill in the various variables. Just press enter and accept the default values. When prompted, enter the project name, client id, and client secret from the email you received.

You will get a ./build directory. Enter the following code:

cd build
pip install -r requirements.txt
./ apm_simple

Once it's complete, you have successfully loaded data into your CDF project.


Make sure you have configured python alias correctly by running which python in the command line. Additionally, it’s also possible to run the script by explicitly specifying which python version to use with the path to the script: python3 ./ apm_simple.


To load the apm_simple example, you can enter ./ apm_simple in the terminal.