Evolving from Reactive to Predictive Maintenance - A Guide to Ensuring that the Plan You Put in Plac
Evolving from Reactive to Predictive Maintenance - A Guide to Ensuring that the Plan You Put in Place Will Help Leverage the Capabilities of ML and AI for the Management of IoT
Years ago data center maintenance was mostly reactive. When a server overheated, it would be repaired. Then we evolved to scheduled routine maintenance based on historical data. Now data centers can anticipate issues before they happen. Welcome to the era of predictive maintenance based on real-time data! This Leaders Lab will focus on use cases of various machine learning approaches, the results that can be expected, and how to implement predictive maintenance strategies in your data center. To achieve a successful predictive maintenance plan using IoT, machine learning and AI, this Leaders Lab will explore steps to get your data center ready for predictive maintenance. Topics include the types and amount of data needed and how to turn it into actionable information, devices and their internal elements requiring predictive maintenance, environmental factors, and best practices for vendor management.
Lab Advisor and Featured Speaker
John O'Connor, Manager of Technology Infrastructure Operations, Bloomberg LP
John O’Connor is Manager of Technology Infrastructure Operations at Bloomberg LP. He sees the data center as a place where many divergent agendas meet their physical reality. In his role, John strives to increase innovation and collaboration to iteratively increase the data center organization’s value to the business. This necessitates an adaptive and dynamic infrastructure as Bloomberg technology helps drive the world’s financial markets. John has been with Bloomberg for 19 years and received his MBA from Northeastern University.
Live Meeting Details
Location: Hilton Meadowlands, Two Meadows Plaza, East Rutherford, NJ 07073
Meeting Room: Conference F/G
Sleeping Room Reservations: +1 (201) 896-0500
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