Use Big Network Data to Predict and Avoid Network Problems

Jonathan Crane, Chief Commercial Officer at IPsoft

Big data continues to be a heavily discussed topic, but generally it doesn’t make its way into discussions about infrastructure and converged systems. But that doesn’t mean big data doesn’t have a role to play in this arena. There is plenty of data generated about enterprise networks. That data resides in log files, but often is simply discarded. Jonathan Crane, Chief Commercial Officer at IPsoft, believes there is a whole new playing field for IT infrastructure: big data in the internal IT department.

By turning predictive analytics inward to track where breaks happen most frequently, IT and network admins can set more accurate thresholds for recurring issues, positioning themselves ahead of any damage.

Crane says, “By applying data analysis around recurring issues in the network or IT infrastructure, organizations can discover problems that should be proactively addressed, thus reducing instances of, say, performance degradation and bandwidth over-consumption.

“Resource availability and performance are the two obvious benefits of applying predictive analytics to IT, but more important is the speed at which results can occur. If you consider the management of trading applications in the financial services market, for example, without the aid of big data analytics, a system administrator could take up to an hour to determine why a new trade failed to execute. Over the course of that hour, the trade itself has reduced in value and the revenue opportunity is lost.

“As IT infrastructure becomes increasingly complex, avoiding this slow infrastructure analysis process will be a key concern for CIOs. With greater volumes of recurring instances, and more decisions made within compressed timeframes, administrators can collect enough data to address the factors that cause those instances, and eventually prevent them from happening at all.”

Source : http://www.convergeyourbranch.com/