Transforming IoT Data into Actionable Knowledge

For the majority of businesses, the main attraction to IoT (Internet of Things) is data and the insight it can provide. It is undeniable that the ubiquitous connectivity of today provides the capability to capture huge amounts of data. For companies who are focused on data alone, it’s an amazing upturn of events. However, it must be remembered that it is only raw data, which can be considered as nothing more than a commodity.

How Data Becomes Useful
In order that data becomes useful, it must be processed into a product that is both useful and consumable. This requires a few steps.

Initially, a connected device that is enabled to capture the raw data you or your organization needs is required. The question is; what do you need to capture? This can include anything from interactions between devices and objects to environmental data.

Once the relevant data has been has been identified and captured, it is then time to migrate it to the cloud so that it can be integrated and processed.

Understanding the Data
Now that the data is in place, usually stored on a cloud server and accessed via an analytical system or platform, it is now time to begin constructing the baseline datasets. Following that step where the initial datasets are in place, the data can be correlated to other sets of data. This is where the fun begins, once all of these initial steps have been completed.

What was once only raw data can now be compressed and analyzed, most importantly, it is now accessible as useful information.

There are quite a few ways to approach this, depending on whether a historical view for trending is needed, or predictive analysis is required. However, regardless of how the data is to be approached, the third step, which is absolutely critical, requires that it is turned into information. Once the information is in place, the most difficult task is still to be completed.

Extracting Insights
This stage is where the data has moved to being information and can finally be accessed as knowledge. For this to be successful the data needs to be presented in such a way that the insight and value it can provide are evident.

The crucial aspect in understanding information as knowledge is having control over the user experience (UX). Data visualizations must provide whoever is using it with the ability to understand what they are seeing, compare it, and finally create actionable insights.

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