Hi, I’m Guntur, a full-time PhD student at UNSW Sydney, Australia. My research is mostly about blockchain and IoT. I am also with Department of Electrical and Information Engineering, Universitas Gadjah Mada, Indonesia.The Data’s Disability
Data is a great tool. But just like other tools, it is good at something, in the other hand, it is poor at other things.
An Op-ed columnist of NYT, David Brooks, alleged his story of a friend of him, who was the CEO of a multinational bank. At that time, he was in a terrible condition: Europe was at a devastating economic recession and he had a branch of his bank in Italy. He had to make a decision whether he has to take the branch out of Italy or keep it stands in the middle of a long-lasting recession, and he didn’t want the Italians think that he is a completely good companion for a good time, and he is going to be disappeared when the bad time run into them. Then, he would be likely to use his powerful data analysis tool in order to help him facing this horrible stake. However, he knew that business is all about trust. Eventually, he kept his branch stands in Italy while his data analysis would probably say that it is an risky decision to do so.
That story shows us that, data doesn’t always help you to get what you really want. Sometime you’d better think out of the box in order not to run out of your business.
Brooks then decomposed his thesis into seven points. Here, I would be underlining one of them that I think it depicts the rest of the points.
Data is poor at handling social things. As you might already know, data is great at handling quantity, on the other hand, it is poor at dealing quality. For instance, computer driven data analysis could easily measure the quantity of social interactions, but not its quality. Computer is not able to cover whether each social interaction has a nice quality or otherwise.
This article was paraphrased from the New York Times.