Peter Beasley

Peter Beasley

Dallas-Fort Worth Metroplex
4K followers 500+ connections

About

Specialties: Experienced information technology entrepreneur-founder, with specialty in…

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Experience

  • Blacks United in Leading Technology Graphic
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    Dallas-Fort Worth Metroplex

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    Dallas/Fort Worth Area

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    Dallas/Fort Worth Area

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    Dallas/Fort Worth Area

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    Dallas

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    Dallas/Fort Worth Area

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    Dallas/Fort Worth Area

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Education

Licenses & Certifications

Patents

  • Behavior-based invention for predicting and avoiding network downtime

    Issued US 8,516,312

    Poor changes to IT systems often result in a loss of performance or downtime. Indeed most IT downtime is caused by changes made to the IT systems by people. Accordingly, models are needed to better predict and identify these unexpected consequences such that they can be avoided, before they happen. The present invention provides such models. The invention teaches systems and methods for identifying and eliminating unexpected consequences of telecom and network change by predicting and/or…

    Poor changes to IT systems often result in a loss of performance or downtime. Indeed most IT downtime is caused by changes made to the IT systems by people. Accordingly, models are needed to better predict and identify these unexpected consequences such that they can be avoided, before they happen. The present invention provides such models. The invention teaches systems and methods for identifying and eliminating unexpected consequences of telecom and network change by predicting and/or identifying 1) risk of failure of a planned IT change, 2) likelihood of success of a planned IT change, 3) people that can be affected by an IT change, 4) systems that can be affected by an IT change, and 4) the otherwise unanticipated consequences of an IT change. This prediction is performed based on, in part, the present and past behavior of the change implementer, the behavior of the organization, and/or the interdependence of the item being changed, as corrected by past predictions and past change successes. The problems stated above, as well as other related problems of the prior art, are solved by the present invention, a method and apparatus for 1) predicting the risk of failure of an IT change, 2) the likelihood of success of an IT change, and 3) identification of the unexpected consequences of that change

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