Back to basics: Data Mining and Knowledge Discovery Process
Once in a while I go back to basics to revisit some of the fundamental technology concepts that I’ve learned over past few years. Today, I want to revisit Data Mining and Knowledge Discovery Process:
Here are the steps:
1) Raw Data
2) Data Pre processing (cleaning, sampling, transformation, integration etc)
3) Modeling (Building a Data Mining Model)
4) Testing the Model a.k.a assessing the Model
5) Knowledge Discovery
Here is the visualization:
In the world of Data Mining and Knowledge discovery, we’re looking for a specific type of intelligence from the data which is Patterns. This is important because patterns tend to repeat and so if we find patterns from our data, we can predict/forecast that such things can happen in future.
In this blog post, we saw the Knowledge Discovery and Data Mining process.