![]() ![]() What is relevant is not only what probability but also when. Prognostics is giving a perspective or an insight or foresight onto what is going to happen when and with which probability. With data analytics methodologies, we aim to reach as good a foresight perspective on that component as possible. That thing could be an industrial asset like a turbine or a pebble crusher, a car, it could be our heart, etc. With prognostic, we are talking about something, which we need to understand prognostically based on data. The key is to get as accurate within that area of uncertainty about the future as possible. In the industrial context, it is necessary to analyze data to glean inside about the future and understand that it is actually under uncertainties that are probabilities. In his career, he has had skated in wrong directions a lot of times but probabilistically, he is going to have skated in the right direction more often than everybody else and that is because he understood probabilities behind the data patterns he was looking at. Concept two, which is usually forgotten, is about probabilities. He pretty much has a data analytical engine in his brain intuitively that understands patterns and identify what is going to happen next. One is pattern recognition or data analytics to understand what is going to happen next. Behind that, actually, are two interesting concepts. In that context, a great well-known quote says “a great hockey player skates where the puck is going to be”. The reason why behind engaging in analyzing data is obviously because we want to learn from the past to know something about the future and be better prepared. There is a lot of talk about data analytics nowadays since we have the data now at our fingertips and the computing part has to do something with it. ![]()
0 Comments
Leave a Reply. |