DATA MINING: THEORY, CONCEPT AND TECHNIQUES
Mustapha Ibrahim1 and David O. Tayo2
1& 2Department of Computer Science
Federal Polytechnic, Damaturu. Yobe State
Email: mustee2004@yahoo.com or babakhalil2012@gmail.com
ABSTRACT
Organizations recently developed transaction processing technology that requires data captures in large amount and match the speed of processing of the data into information which can be utilized in making decision. Data mining, the extraction of hidden predictive information from large databases, is a newly powerful technology with great potential that help organisations to project on the vital information in their data warehouses. Machine learning is used for statistical and visualization techniques to discover and present knowledge in a form which is easily intelligible to humans. Data mining tools are used to predict future trends and behaviours, allow businesses to make proactive, knowledge-driven decisions. Most organisations received and store large volume of data about their businesses and most of these data are not used to analyse useful information form it due to inability to derive a viable information form it. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Data mining tools support organisation to ascertain valuable information from the data set. To deliver a large volume of data in term of speed and accurate the use of data mining tools becomes paramount for effective and efficient useful of information of future prediction. Financial organisations in these days make use of computer as a tool for adequate and effective storage of information or data.
Key words: Data Mining, Data warehousing, machine Learning and Tools and Techniques
