Splunk Doubles Down on Machine Learning Analytics

The application of machine learning to predictive analytics continues apace as a way to improve IT operations, data security and business intelligence. Among those offering frequent platform upgrades is real-time "operational intelligence" specialist Splunk Inc., which this week rolled out the latest versions of its IT, security and analytics packages that seek to "operationalize" machine data. San Francisco-based Splunk (NASDAQ: SPLK) said machine learning is integrated as a core capability in its latest package of IT, security and analytics offerings in the form of packaged or custom algorithms intended to leverage growing volumes of machine data. Use cases for its enterprise, IT services, security and user behavior analytics products include: "focused investigation" of IT and security incidents to detect data patterns and anomalies; reducing "alert fatigue" by identifying normal patterns for specific use cases; proactive maintenance; demand forecasting, managing inventory; and adjusting to changing business conditions by analyzing historical data. "The enterprise machine data fabric is the foundation for managing and deriving insights from that data at scale," Splunk President and CEO Doug Merritt asserted in a statement.