Advances in predictive analytics expand organizational data intelligence
When it comes to data analytics, most organizations have historically focused primarily on descriptive and diagnostic capabilities. Descriptive analytics explains what is happening in an IT system and uses analysis levers including analyzing trends, mining patterns, and detecting changes and anomalies. Diagnostic analysis encompasses functions including critical path analysis, bottleneck analysis, fault propagation models, and root-cause analysis to explain why something is happening in the system.
With an increased focus on instrumentation and observability, allied to significant advances in AI, enterprises are now looking beyond simply what happened and why, and seeking to apply advanced intelligence to draw valuable predictive insights from data. IT leaders are looking for insights that can inform them about what is likely to happen in the future and how to prepare for it, for example:
