Glossary¶

Data Model

A data model organizes data elements and standardizes how the data elements relate to one another. [1]

Entity

Entities are used to identify the primary key on which feature values are stored and retrieved.

Feature

A feature is an individual measurable property. It is typically a property observed on a specific entity, but does not have to be associated with one. For example, a feature of a customer entity could be the number of transactions they have made on an average month, while a feature that is not observed on a specific entity could be the total number of transactions made by all customers in the last month.

Training-Serving Skew

Training-serving skew is a difference between performance during training and performance during serving. This skew can be caused by:

• A discrepancy between how you handle data in the training and serving pipelines.
• A change in the data between when you train and when you serve.
• A feedback loop between your model and your algorithm.

1. https://cedar.princeton.edu/understanding-data/what-data-model