Big data analytics are one of the hot new trends of the data science field. Marketing firms have already recognized the value of locating subtle nuances of meaning hidden inside huge pieces of information. Now those same techniques of analysis are being applied to network monitoring.
What Big Data Does
There is no one definition for what big data is, but three theoretical aspects characterize these massive sets of data: volume, velocity, and variety. Essentially anything that requires a significant portion of your processing power to manage can be classified as big data.
Data scientists have techniques for collecting and managing such information. They discover meaning in the ocean of information that would otherwise be overlooked. Networking monitoring techniques must change to incorporate these methods. Big data analytics allow networks to improve the performance and reliability of enterprise networks.
Changes in Networking Structures
Enterprise networks used to be simple. They had a single programming language, and ran a single operating system on a single server. Updates were infrequent and the security software did not require constant patching.
Responding to business demands for more dynamic computing solutions, modern networks are vastly more complex. They are an interlinked set of devices, operating systems, and programing languages. They also include virtual machines that function alongside the more traditional architecture. These systems have multiple points of access and must support mobile devices and shared information across platforms.
The sheer complexity of these systems produces a volume of data that is difficult to monitor or control. The type of data varies dramatically across the many different formats, and it must move rapidly without interruption. These qualities make networks more difficult to monitor, control, and secure.
How Big Data Is Being applied to Network Monitoring
Network monitoring is a prime candidate for big data solutions. These new methods are making it possible to monitor a network in real time and respond to threats dynamically. The software that protects a complex network must now be able to adapt to a cyber attacker’s rapidly evolving attempts to beat the system.
Big data also enables a system to balance loads across computing devices. Instead of relying on the processor of a single machine, a virtual machine can handle a request for services from a remote location. It can filter the data better to give network monitoring teams the ability to focus and develop strategies for eliminating unnecessary data streams. Real time analysis powers automated responses which improves security and reduces downtime.
These features increase the performance and reliability of a network. Big data makes it possible for network monitoring teams to fulfill their mission. Expect more developments as the data sciences field continues to mature.