Concept of Data Mining
Data Mining means extracting or mining the knowledge from the voluminous data. It is also sometimes referred as knowledge mining from databases, knowledge extraction, data or pattern analysis, data archaeology, and data dredging. Many people believe that Data Mining and Knowledge Data Discovery i.e. KDD are same. Knowledge Data Discovery and Data Mining are vast topic and also very interesting subject in Computer Science and Engineering here at MANIT Bhopal. Working of search engines like Google also utilizes these concepts Data Mining. It can be a very good research topic especially for those who have good hold in DBMS. Knowledge Discovery involves sequence of processes. They are as follows:
- Data Cleaning: This step involves removal of noisy and irrelevant data.
- Data Integration: It involves the process of combining multiple data sources
- Data Selection: In this step relevant data are retrieved from the Database so that they can be analyzed.
- Data Transformation: This is very crucial step in which the selected data for analysis is further used and transformed into desired and appropriate form. Particularly in multidimensional database the irrelevant dimension is removed.
- Pattern Evaluation: Here we identify to identify the truly interesting patterns representing knowledge based on some interestingness measures
- Knowledge Presentation: This is the final step in which the mined knowledge is represented to the end user in the form of bar graphs or spread sheets etc.
Usually the first two steps are known as Data Preprocessing when combined. Though there are various other concepts which is needed to understand the complete process nicely such are Data Warehousing, OLAP Technology, various algorithms for analyzing the data etc. But the space will not suffice due to vastness of the topic. If you want any help in above concepts please leave the comment. Here at NIT-Bhopal we are recommended the book of author named Kamber for this subject. The book is vast and interesting but requires good knowledge about the DBMS concepts.
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