ML can certainly boost the amount of data that IT organizations pay attention to, and thus get more insight and proactive value out of their data. The ability to organize, correlate, and holistically view related anomalies across data types is critical to problem isolation and root cause identification. It reduces application downtime and limits the possibility of problem recurrence.

In the next chapter, Chapter 5, Security Analytics with Elastic Machine Learning, we will see how ML can benefit those that have more of a more security operations focus by allowing us to distill out bad behaviors and anomalous activities that might be indicators of compromise or malice.