In BigQuery, partitioning divides a table into separate segments based on a column like date or integer range, helping BigQuery scan only required partitions. Clustering organizes data within those partitions by sorting rows based on selected columns such as customer ID, country, or product category. Partitioning reduces the amount of data scanned at a high level, while clustering improves query efficiency inside the scanned partitions by minimizing the data blocks BigQuery needs to read.