What should you do to reduce the cardinality of a column in a Power BI dataset?

Reducing the cardinality of a column in a Power BI dataset involves decreasing the number of unique values within that column. Cardinality refers to the uniqueness of data values contained in a particular column. High cardinality can lead to performance issues, such as slower query times, as Power BI needs to store and manage more unique combinations of data.

By reducing the number of distinct values, you effectively lower the complexity of the dataset. This can be achieved through several methods, such as consolidating categories, grouping values, or eliminating less significant data points that do not contribute to the overall analysis. For instance, if you have a column with many unique identifiers like customer IDs or product SKUs, it might make sense to categorize these into broader groups to improve performance.

In contrast, the other choices do not directly address the core issue of cardinality. Adding prefixes or suffixes merely alters the values without actually reducing their number of distinct entries. Replacing null values with zero changes the data but does not inherently lower the diversity of entries in that column. Therefore, the most effective way to manage and improve performance regarding cardinality is indeed to reduce the number of distinct values in the dataset.