Data Mining Prediction

How Exactly Data Mining Tells Prediction?

There are countless publishing that you can read on the internet about data mining. But, upon reading those articles posted on different platforms, most of them are just saying the main concept of data mining.

The factors, types and even the procedures on how data mining is being utilized and so on, with this, we sense that there is something lacking in it.

Now the question, how exactly is data mining tells prediction or the things that going to take place next? Sounds like a good question right?

Although on some of the content that we managed to read stated some good answers the question and some did not.

The method that is utilized in order to perform a superb data mining is known as modeling.

To give you an idea about modeling, this is merely an action of building certain model suited for a specific scenario in which you know the specific answer to the problem and apply it on the actual situation.

Let us say, you are looking for something eg. Sunken ship with lots of treasures in the Pacific Ocean, the first thing that you are going to do is to do some research on the ship routine.

After getting the needed information you then identified the route, the places and the climate of the places the ship travels.

By having those data you will now have the idea to which places might be sunken. So you build your model based from the location of the ship. The model now will be used for you to sail in search for the ship with treasure with hopes that you can finally find the treasure.

The simple act of building a model is something that most of us are doing for long time, in fact even before data mining or computers where created, modeling is already there.

The comparison of the past and today is not that much different to what people build its models.

Basically, computers are preloaded with tons of data based on situations wherein answer is already known and software on data mining at the same time should run on that data and still the characteristics is applied in order to get the model. A model is created in order to be used as answer to certain scenarios that are still unknown. Let us have another example, assuming that you are one of the marketing directors of a big telecommunication company and you are planning to acquire new long distance features to clients.

You can simply go out in the community and give out coupons to them, just as sailing on seas randomly looking for treasure. But if you are aiming for better results, there are other opportunities that you can do besides from random, you can use the database of the company and build a new marketing model for it.

As marketing director, having access to information on your customers like age, credit history, and calling usage is easy. The good part of it is that, the information for your prospective clients are already there.

The problem now is the calling usage to your competition and the concentration is on the amounts of usage.

By simply building your model, you will have now an overview of what your customer desire and why, in which the information will be integrated to the model to create a successful prediction.


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