There are seven key capabilities, each with their own development challenges, that ISVs should be aware of when wanting to build entity resolution models into their offerings.
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Watch this video as Jeff Jonas explains how an Entity Centric Learning™ entity resolution system matches data faster, more accurately, and is smarter overall when compared to data matching or record linkage systems.
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In this video, Jeff Jonas explains how easy it is to get immediate benefits from integrating entity resolution with just a few API calls, whether your software runs on premises, in a private cloud, or as a service.
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ISVs trying to decide whether to build or buy better data matching or relationship detection for their commercial software product can get advanced and affordable entity resolution in a couple of sprints.
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Watch this video as Jeff Jonas unpacks why continuous entity resolution is so important for making accurate business decisions.
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In this video, Jeff Jonas explains some of the tools the Senzing offers for open source entity resolution.
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Watch this video as Jeff Jonas goes through specific examples of what can happen when performing fuzzy matching for advanced data matching and relationship detection.
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In this video, Jeff Jonas discusses how entity resolution enhances machine learning outcomes.
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James Maguire speaks with Jeff Jonas on the challenges of duplicate entries in a data repository and how to overcome them for optimum performance of your data analytics platform.
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In this video, Jeff Jonas describes entity resolution is important for improving outcomes.
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Mike Barrett, head of anti-money laundering products, discusses the business and technical reasons why NICE Actimize decided to embed Senzing entity resolution into its AML product suite.
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In this video, Jeff Jonas explains the ease of adding entity resolution capabilities from a third party to your product.
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