Collecting IoT data is easy. Knowing which IoT data to collect and save is the key. The challenge most organizations face today is determining what data is relevant, and whether or not the data they need is already being generated. This is the right place to start. Once these two things are determined, organizations can take the next logical step – which is to be able to learn from this data. This next step requires taking full advantage of the benefits that computing at the edge provides. The following article cites some good examples of strategies and solutions that companies can use to separate the wheat from the chaff when it comes to IoT data.
The internet of things is going to generate a lot of data. IoT is all about data, and how cheap computing, ubiquitous connectivity, and low-cost data-generating sensors change the depth with which we can see the world and its processes around us. But the promise of all of that data confuses people.
At every conference I attend, someone inevitably gets up on stage to talk about how his company has managed to transform its business with better data. And they note that one of the essential steps in that process involves gathering tons of data from sensors and then sending it to the cloud, to something called a data lake. It’s the IT equivalent of hoarding. And it is not necessary.