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What is Network Analytics? Explained.

Mohammed NaserMohammed Naser

By giving more profound insights into how performance and usage, network analytics can aid improvement of security, troubleshoot minor issues, predict traffic, spot potential trouble, and perform in-depth audits and investigation. However, many are not familiar with the basics of the concept. Here is a look.

What is Network Analytics?

Network analytics is the application of essential data tools and principles to manage and secure data networks.

To use network analytics to its potential, businesses require infrastructure that can give optimal performance and data utilization for the network. The data can consist of low-level information, latencies, and collision and packet drop rates. Higher-level information can include packets influenced by specific security policies, with their origin from any given address or headed to any given address. Enterprise also requires systems for collecting, storing, and analyzing this enormous quantity of network data.

Typically, network analytics is used by larger organizations. Most of the time, medium or large enterprises use cloud services to consume network data analytics. Enterprises with highly complex networks or advanced security requirements might adopt network analysis tools. When using these tools gets more accessible, standardized, and less costly, the technology will move towards smaller networks.

Additionally, network analytics will become more critical and widely deployed with the rise of network security. With advancements in technologies like IoT and microservices, the number of player networks is expected to grow significantly, leading to vast amounts of network data.

Predictive Analytics

Network and security operations could greatly benefit from predictive network analytics. The rapid infusion of AI and machine learning in network analytics accelerates the ability to predict potential issues based on current network data. These emerging techniques allow tools in more data ingestion across more comprehensive types of data from a broader range of sources. Network teams will also be able to identify and extrapolate changes in baseline and see both historical and future trending. Over time, predictive network analytics tools could detect forthcoming changes in network performance.

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