What is a limitation of using joins between datasets?

Using joins between datasets can indeed increase processing time, which is a key limitation. This increase in processing time is primarily due to the complexity associated with matching records from multiple datasets, especially as the size and the number of records grow. When datasets are joined, the system needs to perform operations such as combining rows based on specified keys, which can involve significant computational resources and time.

While other options may suggest limitations related to joins, they do not accurately reflect the operational constraints faced when executing joins in a data processing context. For instance, joins can be made between datasets from the same or different sources, which means the idea that they can only operate on datasets from different sources isn't a limitation. Furthermore, while it's important to manage data quality, a specific field to avoid duplication isn't a universal requirement across all joins, though it may be advisable in certain scenarios. Similarly, while data cleansing can be essential in preparatory workflows, joins themselves do not inherently require additional data cleansing—it depends on the nature of the data involved. Thus, the most appropriate limitation regarding joins is certainly the potential increase in processing time.