Data contextualization means adding related information to any data to make it more actionable. Trends, patterns, and correlations stand out against a background of context. When you start integrating data into various sets that provide context for IT events, you get a lot more value from the data. Contextualization is crucial to delivering and maintaining quality services. But, the seamless implementation of incident management process cannot be formulated overnight. You need to discover incidents that affect system performance, availability, and productivity with full-context alerts across your IT operations monitoring systems.
Machine-driven operations can automatically pinpoint incident root-cause to fix an outage and minimize downstream impact before it affects service delivery. Automated context can also predict and evaluate service impact by experimenting with what-if models. It will reduce firefighting and restore services faster.