In music or any data-related field, enriching data from an external source is a common still tedious task. External data can come from open datasets like wikipedia, web crawling (if legal) or any other data sources. The main idea is that you own locally your dataset, public or not, and you want to enrich it with public and rich data. In music, Musicbrainz and Discogs publish such datasets, that can be used for matching. As I recently worked with the RISM dataset (Répertoire International des Sources Musicale), I will use this as an example, to match person entities.
However, the algorithm I’ll build for you is source and field (and language) agnostic.