Data matching has always been a substantial part of the capabilities in data quality technology and have become a common capability in Master Data Management (MDM) solutions.
We use the term data matching when talking about linking entities where we cannot just use exact keys in databases.
The most prominent example around is matching names and addresses related to parties, where these attributes can be spelled differently and formatted using different standards but do refer to the same real-world entity. Most common scenarios are deduplication, where we clean up databases for duplicate customer, vendor and other party role records and reference matching, where we identify and enrich party data records with external directories.
A way to pre-process party data matching is matching the locations (addresses) with external references, which has become more and more available around the world, so you have a standardized address in order to reduce the fuzziness. In some geographies you can even make use of more extended location data, as whether the location is a single-family house, a high-rise building, a nursing home or campus. Geocodes can also be brought into the process.
Handling the location as a separate unique entity can also be used in many industries as utility, telco, finance, transit and more.
For product data achieving uniqueness usually is a lesser pain point as told in the post Multi-Domain MDM and Data Quality Dimensions. But for sure requirements for matching products arises from time to time.
In the old days this was quite difficult as you often only had a product description that had to be parsed into discrete elements as examined in the post Matching Light Bulbs.
With the rise of Product Information Management (PIM) we now often do have the product attributes in a granular form. However, using traditional matching technology made for party master data will not do the trick as this is a different and more complex scenario. My thinking is that graph technology will help as touched in the post Three Ways of Finding a Product.