Exploring default fuzzy matching in Power BI

Power BI provides advanced data matching and clustering capabilities through its fuzzy matching and fuzzy clustering tools. These tools are particularly useful for data analysts who need to compare and merge items from separate lists based on their similarity.

Fuzzy matching enables you to merge two tables in Power Query by identifying and matching similar items. On the other hand, fuzzy clustering leverages a fuzzy matching algorithm to group data points with similar values together. This is achieved by mapping the value of each column to the best-matched group.

Power Query provides users with the flexibility to apply both fuzzy matching and fuzzy clustering options during data transformations. Fuzzy matching options are available when merging two tables, while fuzzy clustering options can be accessed when adding a new column.

While Microsoft provides a simplified description of the algorithms used by Power BI saying that...