Knowledge Discovery Process through Data Mining: A Technical Approach for Data Analysis
|Sk.Abid Hussain, Ch.Venkateswarlu
|Related article at Pubmed, Scholar Google|
Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make valid predictions. The first and simplest analytical step in data mining is to describe the data - summarize its statistical attributes (such as means and standard deviations), visually review it using charts and graphs, and look for potentially meaningful links among variables. In the Data Mining Process, collecting, exploring and selecting the right data are critically important. Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavouring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Knowledge Discovery in Databases (KDD) is the process of identifying valid, novel, useful, and understandable patterns from large datasets.