MatchUp Component for Contact Zone
Advanced fuzzy matching for a single view of data assets
MatchUp makes use of a tool box of advanced fuzzy matching algorithms, deep domain knowledge, and a custom lexicon to granularly identify matches between names and nicknames, street addresses and abbreviated addresses, companies, cities, states, postal codes, phones, emails, and other contact data components.
- Compare records in one or more databases at once and process entire lists
- Use two input pins (i.e. source and lookup) to suppress duplicates or list out intersecting records
- Recognize any combination of over 35 data types, including ZIP Code, Address, and Last Name, Email Address, Social Security Number, and more
MatchUp employs state-of-the-art fuzzy matching algorithms, including:
- Dice’s Coefficient
- Longest Common String
- Frequency Near
- MD Keyboard
Identify Obvious and Not So Obvious Duplicates
MatchUp’s advanced fuzzy matching algorithms can identify obvious duplicates like:
Create Your Own MatchCodes
And not-so-obvious duplicates like:
With MatchUp you can set up your own matching rules (called Matchcodes) in any combination of over 35 components from common ones like Zip Code, Address, and Last Name – to not-so-common elements like Email Address, Company, and Social Security Number. You can even specify your own proprietary data component, such as an account number, using the user-interface-driven MatchCode editor.
Regular Expression Builder
MatchUp comes with a Regular Expression builder that helps users with RegEx syntax and enables processing of multiple expressions in a single pass. Built Regular Expressions can be saved in a library for reuse. Cleansing the data prior to matching is a crucial step to get the most accurate results.
Maintain Full Lineage Through Pipeline Metadata
MatchUp outputs full metadata to provide lineage on what columns were compared and match rules used.