The first zone is where the input dataset is added to the project and initial transformations are made to the data.

![Data Splitting.png](LaToaXrWGyTJ)

The [input dataset](dataset:applications) is chosen by the user through the [Dataiku Application](article:15) interface. It must contain a ```credit_event``` column and an ```id``` column, and all other columns will be used as features to predict the creditworthiness of the applicant. The mapping is defined in the Dataiku Application, along with the set of sensitive variables, these columns will be removed from the core analysis because these variables cannot, for regulatory or ethical reasons be included in the model. More information about the Responsible AI aspect of the project can be found [here](article:3).

Then, the dataset is [split](recipe:split_applications_joined) between a training dataset and a test dataset. The training dataset will be used to run all the feature manipulation and model building while the test dataset will be kept for the final evaluation.


