Why You Need AI in Your Network Analytics

It’s been said that every company is now a data business, and that means that every company is now also an analytics business. Why? Data does little good in its raw form. It needs to be processed so that it becomes insightful, actionable information – in other words, it needs to be analyzed. We think that the only way to promote optimal operational efficiency and get the best from your data and analytics is with the help of Artificial Intelligence (AI).  Here’s why.

The Leaning Tower of Data

How much data does your network produce each day? Even for small businesses, the volume is skyrocketing every year. More and more processes are now digital, there are constantly new devices connecting to the network (hello, IoT), and there are always questions about how to streamline business processes and optimize the network so that downtime is ultimately eliminated. To answer these questions, you need data and analytics from every network connected device, all applications, backend and frontend infrastructure, and the RF environment. 

To really drive home how much data is being used here – you don’t just need analytics weekly, or from the morning rush. You need constant, real-time analytics, 24/7. Yes, this includes when no one is onsite. The network is still “on” even when no humans are present. Its dynamic ecosystem can change at any time, thanks to anything from a device update to changes in a neighboring network to a hacking attempt. You need analytics from all times in order to completely understand your network’s health and performance and optimize it.

Additionally, you need historical analytics. When viewed over time, these analytics reveal network trends and greatly boost efficient budget and capacity planning. With them, you always know exactly what your network needs when it comes to updates and upgrades, even if real-time analytics don’t reveal any in-the-moment, adverse changes.

So, you can see why we recommend an AI-based analytics system. It might be possible to hire enough network engineers to have them monitor the network 24/7, but it isn’t logical. It also isn’t feasible for engineers to analyze thousands of bytes of data in real-time and provide actionable intelligence on the spot. For that, businesses need AI.

What “type” of AI do I need?

As AI has continued to become more popular in the last few years, there are different analytic platforms you can adopt that use this technology. When it comes to your wireless network, we recommend working with AI that will not only provide data analysis, but will also automate certain processes.

Specifically, we like to automate testing. It’s a key pillar of our own AI-based platform, the Wireless Intelligence Platform (WIP), which tells you how important we find it. We’re firm believers in scheduled, consistent testing because it’s one of the best ways to constantly keep eyes on the network, and prevent any nasty surprises from bringing your office to a halt – even a short one. By automating this process, you can more easily scale testing, and you remove a task from your IT team, freeing them up to focus on other critical responsibilities. Our platform, WIP, runs tests as often as every 10 minutes and automatically alerts IT if a test fails in any way or falls outside previously established parameters. This gives IT instant access to everything they need to address a failure, as well as providing confidence that the network is running smoothly unless they are otherwise notified.

Running tests on a scheduled basis will generate a lot of data, but with an AI-platform monitoring and analyzing everything, this isn’t a problem. In fact, the more data the better as you can be sure you know everything there is to know about your network, and can therefore optimize it efficiently and effectively.

What do AI-based analytics provide?

Depending on the platform you choose, you will get a number of crucial insights, including:

• End User Experience
• Real-time health and performance of all applications and infrastructure
• Network usage and performance trends over time
• Airtime and client utilization
• Device capabilities
• Security updates

Platforms should monitor the entire network ecosystem, 24/7, use AI-engines to identify any issues, and translate all data into actionable intelligence. One of the key benefits from using these platforms is providing IT with instantly usable information. When IT is asked to resolve an issue, they first must identify the root cause before they can move onto resolutions. This identification phase can take minutes or hours, depending on the complexity of the problem. For example, if a problem is intermittent – as many are – it is incredibly time-consuming for IT to sit and watch the network, waiting for the issue to occur at an unknown moment so that they can capture the necessary data to resolve it. 

With an AI-based analytics platform, none of this is necessary. IT can focus on other mission critical tasks, trusting that the platform will provide an instant alert to any detected issue, with the root cause already identified. Teams using WIP also receive suggested actions for resolution. This drastically reduces the Mean-Time-to-Resolution.

As WIP monitors the network in real-time, IT can resolve issues as soon as they occur, rather than waiting for end users to alert them. This allows for many issues to be resolved before end users are ever affected, streamlining network performance and protecting all business processes from downtime or other challenges.

Businesses using WIP also have access to its historical analytics. These analytics provide health and performance trends over time for APs, client distribution, and airtime and client utilization. Automatically created and saved in graph form, they can be downloaded and easily shared. With these analytics, your business can see exactly how its network is changing and what needs to be done to keep it running ultra-reliably into the future. These analytics give business management teams the exact information needed to optimize their network, rather than requiring them to look at general trends and make assumptions based on that information.

Finally, WIP is vendor agnostic.  This provides future-proofing against ever-changing technology. Whatever platform you work with should promote long-term network optimization and grow with your company, rather than become less useful as time goes on and your network changes.

AI-Analytics: Make Sense of Your Network, Fast

With network health and performance depending on the analysis of thousands of data packets every minute, companies should bring AI-platforms to the forefront of their analytics solutions and provide IT with the support they need to optimize networks more efficiently, now and into the future.