Information systems! What a ride! One may wonder how raw data is processed and delivered as meaningful information. One may also wonder where this process takes place and why…
Raw data can range from numbers, instrument readings, figures, etc all from a primary source. Usually when this data is raw, it is hard to understand what it all means. Luckily, it can be processed into meaningful information. This process almost takes a “step back” to see the bigger picture.
For example, if someone was walking down a busy suburban street in a lower-class neighbourhood and asking pedestrians as they walked by to partake in a survey about the satisfaction they had about their city, it might look a bit like this:
10 people interviewed
Pedestrians happy in their city – 3
Pedestrians unhappy in their city – 4
Pedestrians who didn’t feel safe at home – 2
Pedestrians who were finding it hard to make ends meet – 1
After surveying a small amount of people (10) in a lower-class neighbourhood about their satisfaction in their city, just under half told they were unhappy, a couple pedestrians told they didn’t feel safe at home, one even told that they struggled to make ends meet and few stated they were happy.
Where this raw data and meaningful information can get out of hand is when it is displayed to the public through social media and news networks. Instead of the meaningful information being given honestly as it is above, it may be presented like this:
After conducting a public survey about city satisfaction, 7/10 people admitted that they were unhappy in their city, didn’t feel safe at home and were struggling to make ends meet.
The news headline won’t bother to include that only 10 people were surveyed, almost half of the pedestrians were happy and where the survey was conducted. It’s important to recognise not only what is presented in a news headline but also what might be missing.
The processing between raw data and meaningful information can be pretty straight forward. It’s important to understand that social media and news headlines don’t always present meaningful and honest information. To avoid the confusion, sometimes directing yourself towards the raw data is worth doing if you want honest answers.