It seems predictive analytics stuff stops short of predicting earthquakes. Irrespective of the data that we feed the application and use the right model, it seems we are still far away from making the right prediction when it comes to predicting the quakes.
Life becomes hard when you have to experience situations like this; for example, earthquakes. It drags down our spirit, abolishes our dreams, ruptures our progress, and make us stand in the life’s cross road; not knowing what to do.
The only hope at the moment when it comes to predicting earthquakes scientifically is through predictive analytics, which is not up to the mark. All those complex models that we have today are not answering one and only question; when that quake hits us? How we can protect our lives and assets from the beastly claws of earthquakes, which rupture everything that is related to basic living?
Even the Box-Jenkins model [time-series analysis], the most popular model, is not helpful to do the needful when it comes to predicting quakes. For predicting, precision matters a lot; and for this we need quality data, which we have when it comes to earthquake stuff.
However, still, we are lacking somewhere! Either we need to increase the scope of our understanding or we do not understand the real-scope of predictive analytics a lot. The latter point raises so many in-depth questions, which affects all the industries across the verticals, which are using and recommending predictive analytics at the moment.