Difference between Data Mining and Knowledge Discovery (KDD)

 Data Mining and KDD are the important terms that related to context of huge data. Before learning the basic difference between them. Let’s have a look on DIKW pyramid.

DIKW: It stands for the Data / Information / Knowledge / Wisdom pyramid. Sometimes it is also referenced as “DIKW Hierarchy”, “Wisdom Hierarchy”, “Knowledge Hierarchy”, “Information Hierarchy” or “Knowledge Pyramid”.

Data is a given fact or a set of qualitative or quantitative variables of a certain issue. These bits of pieces values are still raw, and is insignificant unless they are collected and arranges in a certain manner which will now give you an information. 

Information then is a collection of data, which can be used to answer a certain question or describe a concept.

Well knowledge and wisdom, are bit different from data and information, since

knowledge is the awareness or the conscious understanding of information or a concept. Thus, knowledge is more on the intellectual or cognitive ability of a being to possess and interpret information.

wisdom is usually defined as the application of knowledge. Wisdom is the used of knowledge to formulate a judgement or to make sense of a certain situation or concept. It is also used for formulate ideas, and the creation of new things.

Example: Imagine the string “WifiPassword”. The string alone is data. Understanding that it is a string is information. Knowing it is your wifi password is knowledge. And using is to access your wireless is wisdom.

Data Mining and KDD:
Data Mining is the process of finding or analysis of data from large amount of data where as KDD is the process of finding the knowledge from the large amount of data by making the use of data mining as shown in figure below.

Conclusion:

The part of KDD dealing with the analysis of the data has been termed data mining. and it is a very crucial step of the KDD process.