What defines high cardinality in a dataset?

High cardinality in a dataset refers to fields that contain many distinct categorical attributes. This means that the variable has a large number of unique values compared to the overall number of records in the dataset. For instance, a column that records individual customer IDs would be considered to have high cardinality because each customer ID is unique.

In analytics, high cardinality fields can significantly impact data processing and analysis, as they may require more complex handling and can affect the performance of algorithms used in machine learning or data modeling. Thus, understanding and identifying high cardinality is vital when working with datasets, especially when it comes to tasks such as feature selection or dimensionality reduction.

Fields with repetitive values would be considered low cardinality, as they do not offer much variety or uniqueness. Data that is not relevant for analytics and fields that are primarily numeric do not specifically pertain to the concept of cardinality, which focuses solely on the distinctiveness of values within a categorical attribute.