August 18


Parse the Internet of Things Data into these 4 Buckets

We are privileged to live in a world where we have access to big data. According to David Friedman, it’s one of the greatest economic opportunities of our time.

Unfortunately, it’s also incredibly difficult to categorize and label. The term “big data” has been used to refer to software tools used to analyze data, data sets which don’t fit in regular databases, or simply, large quantities of data. The truth is, big data is all these things. Which is why we need some more modern qualifiers.

This is where the Internet of Things (IoT) comes in, because it will increase our ability to analyze and measure real world happenings in a way that’s valuable long-term. However, in order for it to be effective, you’ll need to separate IoT data into four different data “buckets.”

The Four IoT Data Buckets

Status – This is the most basic type of IoT data, and can be used as material for more intense analyses.

Location – As the name suggests, location data tracks where product is in real time. Unlike GPS however, Location data needs to work well indoors as well as out.

Automation – This data is handy for running internal systems that humans can’t monitor 24/7 – i.e. air conditioning and central heating.

Actionable – Essentially, actionable data is “status data with a follow-up plan.” It’s data that can be used to create effective solutions to often difficult problems.

One of the many benefits of IoT data is the feedback loop it creates between customers and manufactures. It allows data to be collected and analyzed in real time, without fear of security breaches or wasted time. Basically, when used wisely, it will drive innovation and increase productivity.

Read more from ReadWrite.

Having a framework for discussing types of data is valuable in both building and assessing the value of a product. Do these four types cover the space adequately, or can you think of a significant category overlooked?



Buckets, Internet, Internet of Things, IoT Data, Product Value, Readwrite, Savvy, Separation of Ideas, Things Data

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