DQO is available on PyPi repository.
If you want to install DQO directly from Git go to this section.
You can also run DQO as Docker container.
To use DQO you need:
To confirm that you have Python installed run the following command
Ability to install Python packages with pip.
To confirm that you have pip installed run the following command
Installed JDK software (version 17) and set the JAVA_HOME environment variable.
To confirm that Java is installed on your system, please run this command:
To ensure that the JAVA_HOME environmental variables are properly set, please run the following command:
Install DQO with pip manager
- Create an empty catalogue where you want to install DQO.
Open a terminal, navigate to the created directory, and install DQO via pip manager
Start DQO application
Run dqo app to finalize the installation. This process may take some time as the DQO distribution will be downloaded and the Python environment will be initialized in the DQO home directory.
After installation, you will be asked whether to initialize the DQO
userhomefolder in the default location. Type Y to create the folder.
userhomefolder locally stores data such as sensor readouts and checkout results, as well as data source configurations. You can learn more about data storage here.
Login to DQO Cloud.
To use DQO features, such as storing data quality definitions and results in the cloud or data quality dashboards, you must create a DQO cloud account.
After creating a userhome folder, you will be asked whether to log in to the DQO cloud. After typing Y, you will be redirected to https://cloud.dqo.ai/registration, where you can create a new account, use Google single sign-on (SSO) or log in if you already have an account.
During the first registration, a unique identification code (API Key) will be generated and automatically retrieved by DQO application. The API Key is now stored in the configuration file.
Open the DQO User Interface Console in your browser by CTRL-clicking on the link displayed on the command line (for example http://localhost:8888) or by copying the link.
Now that you have installed and opened DQO, it is time to connect your first data source.