4. Smarter Tools
Along these lines, all tools and programs will become grow smarter with 'experience', and require less input from the people running them. Predictive capabilities will be built directly into analytics tools so that they can perform their own predictive analytics. For example, software might be able to read all the available data it collects, then determine the best prediction interval on its own.
These tools could also assist capacity planners, who look at historical growth rates and plot those rates going forward. Software could calculate its own historic growth rate and then apply that going forward, saving you from having to do that work yourself.
5. Big Data Will Have a Big Influence
Big data has always been a crucial component of predictive analytics, and while algorithms and analytics are beginning to steal the spotlight, data collection remains a crucial component of any IT strategy. As the IT world moves away from time series and performance data and towards sources of information like unstructured log file data, big data and the ability to process it will become more and more important. A truly successful IT optimization effort should recognize the value of big data and work to integrate it into all data analytics.
Predicting Your IT Future
If predictive analytics isn't already a central part of your organization's IT strategy, it should be integrated as soon as possible. Not only does it can help determine the configurations that best ensure continued IT health, it can also protect against risk by predicting what problems might occur and when.
As predictive analytics develop and their level of precision rises, this already useful tool can save companies even more time and money, and should be an integral part of any IT department's toolset.
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