Personalize Dataset

An AWS Personalize Dataset is a container that stores data used to train and deploy personalized recommendation models. It is created within a dataset group and is associated with a specific schema that defines the structure of the data, such as user interactions, item metadata, or user metadata. This dataset is essential for building recommendation solutions, as it provides the foundation for training models that generate personalized experiences.

aws.personalize_dataset

Fields

TitleIDTypeData TypeDescription
_keycorestring
account_idcorestring
creation_date_timecoretimestampThe creation date and time (in Unix time) of the dataset.
dataset_arncorestringThe Amazon Resource Name (ARN) of the dataset that you want metadata for.
dataset_group_arncorestringThe Amazon Resource Name (ARN) of the dataset group.
dataset_typecorestringOne of the following values: Interactions Items Users Actions Action_Interactions
last_updated_date_timecoretimestampA time stamp that shows when the dataset was updated.
latest_dataset_updatecorejsonDescribes the latest update to the dataset.
namecorestringThe name of the dataset.
schema_arncorestringThe ARN of the associated schema.
statuscorestringThe status of the dataset. A dataset can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS
tagscorehstore
tracking_idcorestringThe ID of the event tracker for an Action interactions dataset. You specify the tracker's ID in the PutActionInteractions API operation. Amazon Personalize uses it to direct new data to the Action interactions dataset in your dataset group.