Data Mining Techniques And Their Applications

2322 Words10 Pages
Data Mining Techniques and Their Applications in Financial Data Analysis Deepika Sattu, 800721246, dsattu@uncc.edu Abstract— Data mining is a logical process that is used to search through large amount of data in order to find useful data [2].There are many different types of analysis that can be done in order to retrieve information from big data. Each type of analysis will have a different impact or result. Which type of data mining technique you should use really depends on the type of business problem that you are trying to solve. Keywords: Clustering, Decision Trees, Classification, Prediction I. INTRODUCTION Data is very critical for any organization, industry or business process. Data which was in gigabytes or terabytes…show more content…
Here are the few typical cases: • Design and construction of data warehouses for multidimensional data analysis. • Loan payment prediction and customer credit policy analysis. • Classification and clustering of customers for targeted marketing. • Detection of money laundering and other financial crimes.[6] II. DATA MINING TECHNIQUES Data mining is a logical process that is used to search through large amount of data in order to find useful data [2].There are many different types of analysis that can be done in order to retrieve information from big data. Each type of analysis will have a different impact or result. Which type of data mining technique you should use really depends on the type of business problem that you are trying to solve. Different analyses will deliver different outcomes and thus provide different insights [1]. Below are the three steps involved to make certain decisions for development of their businesses [2] 1. Exploration: In the first step of data exploration data is cleaned and transformed into another form, and important variables and then nature of data based on the problem are determined. 2. Pattern Identification: Once data is explored, refined and defined for the specific variables the second step is to form pattern identification. Identify and choose the patterns which make the best prediction. 3.
Open Document