Which type of join includes all rows of both data sources, including nulls for non-matching ones?

The correct choice is a Full outer join. A Full outer join combines all rows from both data sources, meaning it returns every row from the first data source and every row from the second data source. When there are no matching records in either of the datasets, nulls are included in the result set to represent the absence of data.

This type of join is particularly useful when you want to ensure that no data is lost from either dataset during the merging process. By including all rows, it provides a comprehensive view, which can be critical in scenarios where it is important to analyze all potential relationships between datasets, even if some data points do not directly correspond to each other.

In contrast, a Left outer join includes all rows from the first data source and only matching rows from the second data source, leaving non-matching rows from the second dataset out unless they pair with the first. An Inner join only returns rows where there is a match between both data sources, effectively excluding all unmatched rows. Similarly, a Right outer join includes all rows from the second data source and only the matched rows from the first dataset, thus leaving out unmatched rows from the first dataset. These types of joins do not encompass the full set of data like the Full outer join does