To reduce the cardinality of a temperatures table while ensuring hourly average temperature analysis, what should you do?

To effectively reduce the cardinality of a temperatures table while still enabling hourly average temperature analysis, using the Group By functionality to aggregate the data is the most suitable approach.

This method allows you to consolidate multiple entries for every hour into single rows that represent the average temperature recorded during that hour. By grouping the data based on the timestamp rounded to the hour, you effectively decrease the number of unique entries—thus reducing cardinality—while maintaining the ability to analyze average temperatures for each hour. This approach is efficient and directly addresses the need for summarized data without losing essential information.

In contrast, creating a column for the start of the hour values may not sufficiently reduce cardinality, as it simply introduces a new column without aggregating the data itself. While disabling query load or removing relationships can simplify the data model, they do not address the need for an hourly average analysis or directly impact cardinality in a meaningful way within the context of this question.