Amazon Personalize datasets are containers for data. There are three types of datasets:
Users – This dataset stores metadata about your users. This might include information such as age, gender, or loyalty membership, which can be important signals in personalization systems.
Items – This dataset stores metadata about your items. This might include information such as price, SKU type, or availability.
Interactions – This dataset stores historical and real-time data from interactions between users and items. This data can include impressions data and contextual metadata on your user’s browsing context, such as their location or device (mobile, tablet, desktop, and so on). You must at minimum create an Interactions dataset.
Each dataset has a set of required fields, reserved keywords, and their required data types, as shown in the following documentation.
The notebook will walk you through an example!
Depending on the domain you have picked, you will find different sample datasets, and the approach we have taken to shape the data.