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Identity Resolution Solution

Informatica’s Identity Resolution technology enables you to search for identities (people, companies, criminals, etc.) within a single database or across multiple sources and languages despite intentional or random variations in the data.

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Identity Resolution:

Who do you know? And what data is associated with their identity?

Success today depends on how efficiently and effectively an organization – whether a commercial entity or a government agency – uses available information.

One of the greatest challenges organizations face when trying to gain a strategic advantage from information is dealing with identity data: the information that specifically and accurately identifies a client, a prospect, a supplier, a taxpayer, a criminal suspect, a company.

By its very nature, identity data is subject to unavoidable error and variation that can compromise the performance of basic identity search and match processes, generating false positives or missing matches entirely. In addition, most large identity databases now contain identity data from multiple languages, countries and cultures that often have different structures, follow different parsing rules, and have different variation characteristics. Also, if transliteration, Romanization, character set conversion and other such transformations are employed, a new class of error and variation is introduced.

The key to overcoming these challenges is technology that can mimic an intelligent business user’s ability to determine a match based on a variety of factors, overcoming spelling, phonetic and other errors and omissions in the data while offering the speed and scale to perform high volume searches quickly against very large databases.

That is what identity resolution technology offers.

Informatica’s identity resolution solutions are based on more than 20 years of experience with real identification data from hundreds of production systems in dozens of countries. They provide the ability to search, match and link identities within a single database or across multiple sources and multiple languages despite intentional or random variations in the data.

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