For a machine to learn, it needs a human to help guide it. This includes defining the organizational priorities and acceptable parameters so data science-driven machine learning process can produce results that matter to the organization. That’s where AIOps comes in. AIOps uses machine learning to derive logics and decisions based on assessment of high quality data.
One of the most important applications of machine learning lies in context generation. As the data availability increases, it becomes imperative to help end users reduce noise from this data based on the context and use “relative noise reduction” to enhance efficiency for humans.