Home > Workload Solutions > Data Analytics > White Papers > White Paper—Cloud Native Splunk Enterprise with SmartStore—Predictive Maintenance for IT Operations > Overview
Predictive maintenance is a maintenance strategy that uses machine learning algorithms, trained with data from IT, IoT, or industrial machines, to make predictions about future outcomes. These outcomes include determining the likelihood of issues, defects, or equipment failure.
Using a combination of data, statistics, modeling, and machine learning, predictive maintenance can optimize when and how to perform maintenance on IT or industrial machine assets. Through this analysis, predictive maintenance helps avoid costly repairs, prevent unplanned downtime, and maximize the utilization and availability of the equipment in service.
Predictive maintenance considers estimated service intervals and data-driven insights based on the measurement of operating conditions to monitor and diagnose equipment issues in real time. As a result, it catches anomalies in automated operations before they become major challenges that could impact the business.