This process also requires highly specialized skill sets. When you’re trying to troubleshoot an issue, it’s hard to figure out an actionable next step this way. They have to manually sift through and compare raw data. Unfortunately, this leads to IT teams wasting a lot of time.
This causes a problem where you have a complex ecosystem of solutions all working separately.
They end up having to purchase a lot of different solutions to get that full picture. These solutions all provide useful information, but businesses need complete, end-to-end visibility. Or it may only report on one piece of the user experience, like wireless connectivity. The solution may only report on the traffic passing through one type of device. There are many solutions that offer some degree of insight, but many operate within a data silo. NetFlow, syslogs, vendor-proprietary metadata, etc.), but also compare and correlate it with other devices’ data. A network analytics solution should not only be able to ingest different types of network data (e.g. Network analytics provides insight into what devices are on the network and how they are communicating with each other.
But let’s take a closer look at what network analytics entails, some use cases, and what types of organization can derive the most value from it. Then, that information is used to make better decisions-troubleshooting decisions, threat remediation decisions, business planning decisions, etc. Simply put, network analytics is the practice of using different types of network data to identify trends and patterns.
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