The CEO of O’Reilly Media and IBM Fellow and Chief Innovation Officer join as Strategic Advisors to collaborate and advise Senzing on its goal of democratizing entity resolution.
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Steve Lohr from the NYT dives into how Senzing technology is used to clean up voter rolls. Since 2012, Senzing has helped the Electronic Registration Information Center (ERIC) identify 26 million people who are eligible but unregistered to vote.
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Ben Lorica interviews Jeff Jonas about big data challenges involving entity resolution including deep learning models and big compute.
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AML Partners announces a strategic partnership with Senzing so organizations can automate the revealing/flagging of non-obvious relationships and other entity resolution concerns.
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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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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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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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Kyle Wiggers of VentureBeat reviews Senzing. With seeded data from the financial industry, Senzing discovers relationships between people, objects, and metadata with a 97% success rate.
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Channel separation is a method that hackers employ to confuse security systems. Senzing detects fraud and insider threat by performing channel consolidation.
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Privacy by Design (PbD) serves as the guiding principle for the General Data Protection Regulation (GDPR) and was authored by Ann Cavoukian and Jeff Jonas.
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