Data Mining and Efficient Exploratory Techniques for Analysing Databases

Title: Data Mining and Efficient Exploratory Techniques for Analysing Databases
Publisher: Guru Nanak Publications
ISSN: 2278-0947
Series: Volume 2 Issue 2
Authors: D. D. Sarma and H. S. Saini


Abstract

There is data explosion in every field of activity. There is a need to turn such data into information and knowledge. Further, we need to mine the data. Thus data mining is (DM) the extraction of inherent and potentially useful information from the data. This involves a number of technical approaches such as clustering, data summarization, classification, finding dependencies, networks, analyzing changes and detecting anomalies. Anomalies could indicate signals and signals need to be extracted. There are techniques in time/spatial and frequency domains to find out meaningful relationships, patterns, trends inherent and to extract hidden information among large amounts of data. These techniques are also employed for decision support, predictions, forecasting and estimation. In this paper, data mining concepts are discussed, as also some of the exploratory techniques that could be applied for extracting signals/information, with applications.

Keywords

Attributes, Data Aggregation, Data Cleaning, Data Explosion, Data Mining, Data Reduction, Data Transformation, Exploratory Analysis, Pre-processing, Noise, Signal, Yule-Walker Equations.

Download Full Text

(For complimentary copy, please contact Chief_editor@innovationjournals.com)