Computers are meant to do one thing and one thing only: Reduce human efforts and help in computation of large sheets of data in short span of time. It doesn’t get any simpler this. However, like all things, with the advent of time scientists have come up with various interesting techniques to help them and other end users extract specific patters and knowledge from large sheets of data compute for it to make reason. This branch of Computer Science which deals with the computation of high end data sets and come up with interesting patterns and scopes is widely known as Data Mining.
The name itself is pretty self-explanatory. Mining of large chunks of data can throw about pretty interesting results which are used by data scientists to solve some of the more complex problems plaguing the world today. But, this theory is not as simple as it sounds. Data Mining makes use of some advanced Computer Science techniques like Artificial Intelligence and Machine learning. Let us look at some of the basic functions which is prevalent in Data Mining:
- Anomaly Detection: Data Mining can be used to detect anomalies in large chunks of data. These anomalies can then be accounted for any unforeseen event and hence proactive measured can be taken.
- Association Rule Learning: In technical terms, it means chalking out relationships between the various variables. In Lehman terms, it means something like this: An online commercial website will keep track of all the goods purchased by a certain customer, establish relationships between them and then perhaps send him attractive deals and offers to woo him in for more business.
- Summarization: This will lead to complete and wholesome audit reports that will give one a good idea about the pattern in between large chunks of data and help him in the computation.