Upload or import data into the Engine
You can watch a quick tutorial here:
In this article, you will be importing data into the Engine to create a dataset.
To get you started, we recommend that you download the German Credit Data from here. This is a public dataset provided by Kaggle which we will use throughout the tutorial.
1. Select a project
In the homepage, select "Your first project". This is an empty project that the Engine has automatically created for you to get started immediately.
Note: Alternatively, you may also choose to create a new project. To understand what a project is, see here.
2. Select New Dataset
In the project page, select "Add new Dataset".
Step 1: Choose Source
The create dataset dialog box will open immediately. Select "File Upload".
Note: For a full list of supported data sources, see here.
Step 2: Import Data
Drag and drop the downloaded German Credit Data csv file into the upload box. Once the upload is complete, click "Next".
Step 3: Configure
Here, click "Next" as the Engine has automatically generated the necessary dataset name and configurations for reading the uploaded file.
Alternatively, users may:
- Choose a different name for their dataset; and/or
- Change the configurations for reading the file.
Note: Configurations available will differ based on the data source. For more information, see Change configurations.
Step 4: Confirm Schema
In the final step, users can review and confirm the dataset's schema. Then click "Create" to complete the process and create your dataset.
Tip: If the selected datatype is incompatible with the underlying data, the sample data will show NULL.
Note: In the Engine, column names are treated as case-insensitive and must be unique.
For more information, see the requirements for column names in the Engine.
After the dataset is created, click "Done". You will be taken to the dataset’s details page, and can follow the next steps from there.
