Stream: Virtual Room 8
Time: 16:30 - 17:30
Anomaly detection is a technique used to identify patterns in data that deviate from the norm. It plays a vital role in proactive incident detection by allowing us to detect potential system failures or other abnormal events before they cause significant damage. In this session, we will discuss the fundamentals of anomaly detection, its benefits, and practical applications for proactive incident detection.
There is currently no attachment for Proactive Incident Management with AI/ML for Anomaly Analytics
Tim Brooks is a Senior Product Manager currently responsible for IBM Z Anomaly Analytics. Throughout his 7 years at IBM, Tim has contributed to the founding of Zowe, integrating Z operational events and topology into the Cloud Pak for AIOps and leading portfolio level initiatives for AIOps on IBM Z. With expertise in agile development methodologies, he enjoys using design thinking to break down complex problems into achievable goals, leading cross-functional teams and helping drive innovation.
Tim Brooks is a Senior Product Manager currently responsible for IBM Z Anomaly Analytics. Throughout his 7 years at IBM, Tim has contributed to the founding of Zowe, integrating Z operational events and topology into the Cloud Pak for AIOps and leading portfolio level initiatives for AIOps on IBM Z. With expertise in agile development methodologies, he enjoys using design thinking to break down complex problems into achievable goals, leading cross-functional teams and helping drive innovation.
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