Data Deduplication

Data deduplication is the process of identifying and removing duplicate records from a dataset. Duplicates arise when data is collected from multiple sources, when the same entity is represented differently across systems, or when pipeline errors cause records to be inserted more than once.

Deduplication strategies range from exact matching (identical primary key values) to fuzzy matching (similar names, addresses, or descriptions that likely refer to the same entity). Fuzzy matching is computationally expensive and often requires blocking techniques - first narrowing candidates by a rough criterion before comparing in detail.

In property data, the same listing may appear on multiple portals with slightly different field values. In retail, the same product may have multiple catalog entries with variant SKUs. Deduplication is a critical quality step for any pipeline that aggregates data from multiple sources.