When engaging in the social media community dealing with master data management an often seen subject is creating a list of important capabilities for the technical side of master data management. I have at some occasions commented on such posts by adding a feature I often see omitted from these lists, namely: Error tolerant search functionality. Examples from the DataFlux CoE blog here and the LinkedIn Master Data Management Interest Group here.
Error tolerant search (also called fuzzy search) technology is closely related to data matching technology. But where data matching is basically none interactive, error tolerant search is highly interactive.
Most people know error tolerant search from googling. You enter something with a typo and google prompts you back with: Did you mean…? When looking for entities in master data management hubs you certainly need something similar. Spelling of names, addresses, product descriptions and so on is not easy – not at least in a globalized world.
As in data matching error tolerant search may use lists of synonyms as the basic technology. But also the use of algorithms is common going from an oldie like the soundex phonetic algorithm over more sophisticated algorithms.
The business benefits from having error tolerant search as a capacity in your master data management solution are plenty, including:
- Better data quality by upstream prevention against duplicate entries as explained in this post.
- More efficiency by bringing down the time users spends on searching for information about entities in the master data hub.
- Higher employee satisfaction by eliminating a lot of frustration else coming from not finding what you know must be inside the hub already.
Error tolerant search has been one of the core features in the master data management implementations where I have been involved. What about you?
Liliendahl on Data Quality 
