Data or Information?

So, do we say “data” or “information”? Aren’t they the same thing?  Well, when we’re talking about Industry 4.0, the transformation of “data” into “information”, they can’t be the same thing or else there would be no need for the transformation.

I’ve been in many discussions with clients, company leaders and software engineers and the terms data and information are used interchangeably.  And, as you’ll see, the discussion is confusing and far from clean because of it.  Additionally, if you’re having a sales conversation with a client, you need to know which he or she is asking for – or is it both? To clear this up, let’s take a look at each one.  

We’ll use the simple example of temperature. I might look at a thermometer, or an app on my phone or look at a screen on a User Interface for a machine, and it says 100 degrees Fahrenheit. THAT is an example of a data point – or “data”. There is no context to it. It is a number and an engineering unit. 

However, if the data we have is 100 degrees Fahrenheit, and the temperature is supposed to be 80 degrees Fahrenheit, we now have “information”. We have put context to the “data”.  In fact, we now know the temperature is too high, and decisions need to be made based on the “information”. 

The terms “data” and “information” are clearly not interchangeable and now we see why doing so is problematic and creates confusion. 

A key enabler for Industry 4.0 is Digital Transformation, which means digitizing ALL data – in real time. No clipboards, no paper, no verbal discussions. And further, equipment must be able to produce data – a lot of data. Temperature, vibration, power consumption, quality, and production rates to name a few.

Once all data is digitized, software systems can be created to generate information through complex algorithms leveraging business systems, analysis, artificial intelligence, and machine learning as some examples.  

The key takeaway is, if a client says they want data transformation, then the requirement is generating, collecting, digitizing and data-basing data. If the client says they want information, then they want software systems that integrate, analyze, and put context to their data – tell them what is wrong or right. These are very different exercises, and illustrates the importance of my last blog, which was to define your terms and avoid quoting a toaster, when the client wanted a waffle iron, and this would absolutely produce that mistake!