Network analytics is a process of using various network data to identify trends and patterns. This network data is gleaned and assessed to enhance the performance, reliability, or security of the network. The data collected can also be used to make better decisions. In a recently published forecast report, spending on network analytics, including artificial intelligence-powered products, is predicted to reach from this year’s US$1.4 Billion to US$3.6 billion by 2024.
The report envisaged that the increasingly making use of 5G, IoT, and cloud are factors that could create a larger market for network analytics. Its processes, however, can be automated; thus, IT staff no longer need to manually look for and troubleshoot problems.
On the 5G impacts, the research company noted that the Swedish networking and telecommunications company Ericsson that projects by 2023, the introduction of 5G would fuel the mobile data traffic in India by five times. Also, in an Intel study, it is anticipated that IoT will be connected to 200 billion devices by 2020.
The latest report further divulges that the complexity of IoT is causing companies to move from traditional network products to AI-enabled network analytics solutions to sustain with the rising IoT deployments and other new cloud-based technologies. Currently, the number of connected devices is also seeing exponential growth, as a large number of devices are being deployed and connected.
How Does Network Analytics Perform?
With the emergence of new technologies, the increasing network complexities are expected to propel the growth of the network analytics market. A software engine in network analytics compares incoming data with pre-programmed models and makes decisions that improve network operations.
That data comes from a wide range of sources, including network, wireless congestion, data speed on a switch port, and the time it takes to access an application from a connected mobile device. Once network analytics is deployed effectively, an operation can scale several devices, clients, users, and applications, while enhancing the overall user experience, with lower operational costs.
From large to small, organizations can derive significant value leveraging network analytics. Although, the bigger and more intricate the environment, the more value companies can get. Since large networks that sprawl across multiple locations and harder to monitor, network analytics here can be constructive for them.
Network analytics encompasses a number of significant technologies, such as an Analytics engine that collects data from the network and compares the current state with a model of optimal performance; AI that feigns intelligent decision making in computers.