IT Operations Management (ITOM)

Critical steps to a successful IT operations analytics strategy

Critical steps to a successful IT operations analytics strategy


IT management these days is like standing in the midst of a catastrophic flood and yet dying of thirst: surrounded by rising tides of data all around you, it can be difficult to use it to your benefit. Data, data everywhere, but no insight to improve how IT thinks.


Across your enterprise IT environment and outside its firewall,, hundreds of devices and applications ceaselessly emit volumes of data, all of it containing information pertinent to the state of systems and critical for problem resolution. Deterministic monitoring and other traditional IT analytics techniques that rely on preselected quality datasets for well-known problems can never capture the full gamut of technologies that are invoked.


But with logs, events and machine data all in play for unknown problems, IT can quickly become overwhelmed with data. In order to ensure you have the right information to solve problems, you need to first collect everything and then face down the challenges of storing, managing and using it all.


So how do you turn all this data into valuable insight?


Watch the webcast:Intelligent IT Ops: Use your data to see smarter options for IT operations” 


4 steps toward rich, progressive IT analytics



To get the key information that IT needs to resolve issues faster, lower IT costs and improve service levels, HP has developed a vision of IT operations analytics with four tiers:


1. Event Triage — Monitoring for known problems on a preselected quality dataset is an essential building block for using analytics to better manage IT operations, enabling guided troubleshooting.,


2. Advanced Correlation — Tools such as visual analytics use statistical algorithms to present heat charts and dynamic graphics to identify inferences and determine inter-relationships. This category of analytics exploits many data types, events, metrics, and topology, as well as machine and log data to generate stream and topology-based correlation for known problems.


3. Log Management — IT Security administrators recognize the importance of collecting, storing, and analyzing data to reactively solve problems they didn’t previously know existed, but powerful global search for all the datasets collected is also an effective analytics strategy for IT Operations. (Read more about HP Operations Log Intelligence here.)


4. Advanced Analytics — Proactively monitoring unknown problems will allow you to surmise from recent trends yesterday what you need to change before something goes wrong. Such predictive analytics builds on the three other types of capabilities to provide a comprehensive view into performance metrics, availability metrics, machine data, events, and logs.


Together, these tools help exploit the rich datasets by turning volumes of raw data into actionable insight, unifying search, reporting, alerting, and analysis across all types of IT data for real-time insight.



Watch the webcast

As physical and virtual machine sprawl grows and hundreds of new technologies introduced each year, it’s tough enough for your IT managers to keep up with even predetermined datasets, let alone the new dynamics of modern IT.


Find out how you can go beyond “reactive IT” and deterministic methods to manage IT operations more effectively for better business outcomes. Learn how to take action in webcast, “Intelligent IT Ops: Use your data to see smarter options for IT operations


Register for the webcast here

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