Data matching has become a crucial element in helping organizations keep their data uniform as volumes of data continue to increase. Data matching prevents the intake of duplicate data, while at the same time enabling the ability to enrich existing datasets with additional second and/or third party data.
Troparé Data Matching enables users to accurately match, combine, and append records referring to a single entity deriving from different data sources, via an easy and self-service workflow.SEE IT IN ACTION
Troparé's proprietary matching algorithms are superior to the standard, generalized matching algorithms most commonly used (our clients will happily testify to this). Each match gets an assigned ‘match score’ representing the exact resemblance between records which can be set to a predefined threshold.
As disparate data sources typically do not hold a common entity identifier, Troparé matching algorithms analyze each individual record’s attributes in search of (partial) identity indicators to determine a match.
Troparé facilitates data appending to avoid the merger of data sources. This allows users to keep a clear distinction between sources while still running analysis against the entire set.
Different elements belonging to the same record (e.g. Troparé, Tropare, Troparé Inc., and Tropare Inc.) get stored in a single record but are searchable by the entire list of names.
Discard duplicate content
Simplify data analyses across multiple data sets
Greatly expand record insights with additional information
Append data without merging
Define precise and intelligent selections for future campaigns
Identify key links between datasets
Increase data accuracy, efficiency, and usability
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