I’ve just got off the phone after speaking to a manager at a global valve company. I’d asked for an update on the company’s status, and he kindly overviewed some of the many product launches that had taken place in recent months.
The conversation then took a – for me – rather unusual turn when he started to talk about digitisation and big data.
To be honest, these were terms that I had to google later on to make sure I fully understood what he meant.
Digitisation, it appears, means the act of transforming data into a digital format so it can be directly processed by a computer.
Big data can be interpreted in several ways: for some people it refers to a stream of data that is so large it is hard to process, for others it is the application of intelligent systems that can interpret that self-same data to facilitate decision-making.
The manager I spoke to kindly put these somewhat abstract concepts into a clearer light.
“In this day and age it is easy to develop smart valves and similar device that generate data. The challenge for the user lies in what to do with that data. That’s why we are going a step further, and developing systems that can generate and also interpret data. So instead of telling the operator that the torque required to operate a valve has increased by 5.5% during a given period of time, we can provide additional recommendations about whether it is safe to continue to operate the valve or whether maintenance needs to be scheduled.”
As you can imagine, this practical example of using big data suddenly made good sense and I’m keen to learn more about it during the upcoming Valve World 2016 Conference & Expo.
After all, this event has proven its worth as a place to network and learn about the latest technologies.
Just glancing through the Advance Conference Programme for example, I can see plenty of expert speakers who I’d like to ask about big data.
And I’m quite confident that the Valve World Expo, with well over 600 exhibitors, will also proe to be a rich picking ground for information.
However, in the meantime, if there are any readers who have insights to share into big data, then I am all ears.