Data Quality and Identity Resolution (White Paper)

Here is a white paper available from Informatica that does a good job at discussing data quality and identity resolution.

Go to this page and register to download:

http://networking.ittoolbox.com/research/data-quality-and-identity-resolution-19104?sp=cm

Here is a brief excerpt about the white paper and Informatica.

Identity Resolution helps meet the challenges of dealing with identity data by emulating an intelligent user’s ability to recognize matches but also to discover connections – between people, accounts, products – that might be hidden in the data.

Data Quality processes have evolved beyond the traditional cleansing of names and addresses. In parallel, the market for Identity Resolution processes has evolved from simple search and match functionality for customer service, fraud detection, and security screening processes to today’s highly accurate, high-performance, real-time, cross-language search and match services across multiple applications. Download this white paper now to learn about how Identity Resolution complements and extends the application of data quality and data integration processes into business applications.
About this Sponsor

Informatica Corporation delivers data integration software and services to solve the problem of data fragmentation across disparate systems, helping organizations gain greater business value from all their information assets.

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1 comment so far

  1. Douglas Wood on

    Informatica’s acquisition of Identity Systems last year certainly created a buzz within the industry. IDS was a clear leader in matching technologies, and that portfolio seems to be fitting in well with the Informatica suite.

    Having said that, there is an important difference to be made between ‘matching’ and ‘identity resolution’. I’ve tried to explain my perspective in the following article:

    http://www.identityresolutiondaily.com/452/does-data-matching-qualify-as-identity-resolution/

    Only an “identity resolution engine” that incoporates both probablistic and attribute-specific techniques, AND offers robust capabilities around non-obvious relationship analysis can be considered as such.


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