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Approximately 70% of data collected by ITOps is not actionable, either due to lack of timeliness or context, and real-time normalized data stored in a data lake is needed to produce actionable data. Also, AIOps tools are often poorly configured and lead to alert fatigue. The benefit to the partner organization is that they will be able to capture actionable AIOps data that can be normalized for Artificial Intelligence (AI) and Machine Learning (ML) analysis. Based on the analysis done by AI and ML interventions can be automatically applied to an enterprise IT system.
Reynard Dela Torre;Ralph Dueck
Richard Schentag;Braden Still-Routley
Information and cultural industries
Red River College
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