Real-Time Data Aggregation and Analysis: A New Era Machine Learning

Abstract

Logs are a key bit of leeway and play a vital role in organizations, for the quickest and most productive approach to transform machine data into performance. Log management is a powerful method that incorporates both analysis and event correlation which gives the underlying driver of any security infringement, that may not be able to figure out, even after going through hours. Machine-generated data are more complicated, unstructured and difficult to analyze. However, it is significant to analyze and optimize the execution of a machine. Splunk is an emerging trend for Machine Learning, which amend data analysis to the next level. Splunk makes simple to tackle the intensity of machine learning to enhance the security and operations by searching, analyzing and visualizing the logs generated from networks, applications, devices, etc. This paper proposes, how the logs are overseen by Splunk to produce real-time perceptions.