Data quality refers to whether the information provided by the sensors is accurate enough to provide meaningful insights. Scalability relates to the ability to collect large amounts of data quickly without compromising accuracy. Both of these problems are exacerbated when dealing with IoT devices.
For example, if you want to monitor thousands of servers, each one needs its own sensor. If any single server fails, then all of those other sensors stop working too.
AI doesn’t just provide answers; it gives you options when dealing with network issues. You may not want to take action immediately after receiving alerts from an NPM. Instead, you might need some additional time to think things through or consider other factors. In these cases, you’ll still receive notifications, but you won’t necessarily see any immediate results.
It matters because it affects the way we operate our business. In fact, according to Gartner, “By 2022, 80% of enterprises will rely heavily on AI-powered analytics to drive operational efficiency.” As mentioned earlier, AI helps reduce human error while automating tedious tasks. So, not only does it save money, it makes people happier!
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