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.
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