As technology becomes increasingly sophisticated, big data is being utilized by businesses across countless industries. The tools that are used are also becoming more advanced – and now sensors are playing a bigger role in data analytics. Defined as “the statistical analysis of data that is created by wired or wireless sensors,” sensor analytics can be used to help companies run more efficiently, better understand consumer needs, improve targeting efforts and much more.
The only problem is, how do you effectively read sensor data and interpret it in a way that’s useful? Here are some techniques.
Identifying events that don’t conform to typical patterns can be highly important in several circumstances. One example pertains to online security where an anomaly could indicate a network intrusion. This would help a company detect a security threat and disarm a situation before it becomes serious. Another example pertains to the healthcare industry where an anomaly in a medical diagnosis would inform doctors or nurses so they could quickly address the issue and potentially save the life of a patient.
Sensor data makes it possible to identify atypical events much quicker and more conveniently than in the past. By looking at a high volume of data where everything is more or less consistent, it becomes easy to spot anomalies, which can be useful in many ways.
A big part of staying competitive in business is being able to spot trends and stay on the cutting edge. Wired or wireless sensors help streamline this process because they can be used to generate large volumes of data, which make it possible to spot overarching trends that might otherwise be difficult. In order to use sensor data in a practical way, businesses can examine data on the large scale and search for noticeable trends that could be indicators of patterns that could influence the approach they choose to take to operations.
There’s no doubt that humans are inherently visual creatures – and one of the best ways to make use of a large body of information is to utilize data visualization tools. While visualization can be used in numerous ways, one of the most valuable is for helping businesses better understand customer behavior and spot opportunities. Data Informed offers a good example:
“Business leaders for a supermarket chain can use data visualization to see that not only are customers spending more in its stores as macro-economics improve, but they are increasingly interested in purchasing ready-made foods.” When it comes to examining data that would otherwise be difficult to interpret, visualization makes it significantly easier and more intuitive.
By understanding how to effectively read information from sensors and data analytics, it minimizes any guesswork. In turn, businesses can take abstract information and transform it into something that’s much more concrete so that it can be used in a practical way. And when you consider the long-term implications, this can have a dramatic impact on operations and put companies in a better position to succeed.