Bob Gourley of CTOvision reviews Senzing. Every organization that has data likely has entity resolution challenges- figuring out who is who and what is what in their data.
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Deepak Rangarao of IBM Analytics/Ecosystem reviews Senzing as a guest blogger. He discusses how Senzing can be used to target identity fraud with up to 100,000 records for free.
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John Breeden II reviews Senzing. Senzing makes connections between elements in many databases, including connections with fuzzy data and purposefully false data. Senzing reassesses previous assumptions in real time.
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Jeff Jonas blogs about the laborious process of manually or automatically searching each individual system to locate data meeting specific criteria. He then explains how entity resolution effectively and efficiently solves these deficiencies.
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John Breeden II reviews Senzing. Senzing uncovers fraudulent activity or uncover accidental data duplication for a financial institution. Anyone with a complex data set can uncover fraud with Senzing® software.
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Jeff Jonas blogs about how bad guys utilize "channel separation" to remain undetected. Senzing uses entity centric learning to “channel consolidate” data, even though bad guys intentionally obfuscate their identities.
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Jeff Jonas blogs about using data to figure out how to ask the right questions. With Data Finds Data behavior, your systems can automatically and in real time flag data that is connected so you can start asking the right questions.
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Venky Rao reviews the Senzing app. He discusses questions that arose during the testing process, his initial thoughts, and the results that the Senzing app discovered from his data.
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