Webinar: Machine Learning & Analytic Approaches for Proactive IT Problem Management

Thu, Jun 15, 2017 11:00 AM CDT{LOCAL_TZ}

In an era of digital transformation, IT must move from a reactive to a proactive stance. Organizations that cannot do this will find themselves unable to respond to the sprawl, scale, complexity and pace of change in digital IT data and technologies. 

A successful response to these challenges will include implementation of automated, advanced analytics and machine learning that bridge IT silos like ITSM and ITOps. 

In this webinar, we will share perspectives and strategies for implementing analytics across multiple IT discipline including: 

  • The difference between machine learning and traditional rule-based systems and why machine assisted analysis and learning are required in the digital Enterprise.
  • Why bridging IT data is critical to enabling pro-activity and real-time responsiveness.
  • A specific use case of proactive problem management in the Service Desk using machine-assisted text analytics to uncover underlying problems driving incidents and overcome inaccurate, misleading or missing ticket categorization data.


Paul Beavers 
VP of Products (R&D and Product Management) 
Performance & Analytics, 
BMC Software

Seth Paskin 
Solutions Marketing Manager 
Performance & Analytics, 
BMC Software

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