Data Mining• Motivation

• Synonym

• Process of DM

• Operation of DM

• DM techniques

• Business Application

• Application Selection

• Current Issues

Motivations for Data Mining• Raw data rarely generates direct

benefits

• Its real value is realized when we extract information and knowledge useful

• Some queries are difficult to generate with SQL– Which records indicate fraud? – Which customers are likely to buy product

A?

Motivations for DM

• Only 5%-10% of the collected data has been ever analyzed to support the decision-making process

• The amount of the data collected in an organization continues to increase, while our ability to analyze that data has not kept up proportionately

Data Mining (DM)• A technique which extracts knowledge

from massive data

• It is also known as Knowledge Discovery and Databases (KDD) – KDD is defined as the overall process

necessary to discover knowledge, while DM is one particular activity which applies a specific algorithm to extract knowledge

– However, these two terms are often used interchangeably

Process of Data Mining

• Extracting knowledge from databases is a five-step process

• The five-step process of knowledge discovery is an interactive, iterative process through which discovery is evolved

Process of Data Mining

• Selecting Application Domain

• Selecting Target Data

• Preprocessing Data

• Extracting Information/Knowledge

• Interpretation and Evaluation

Operations of DM

• Classification

• Regression

• Link Analysis

• Segmentation

• Detecting Deviations

DM Techniques

• Machine Learning– Induction– Conceptual Clustering

• ANN

• Statistical Techniques

• Example-based Methods

Business Application

• Marketing– Market Segmentation– Market Basket Analysis– Trend Analysis– Sales Prediction

• Finance– Bankruptcy prediction– Credit approval

Business Application

• Finance– Bond rate prediction– Mutual fund selection

• Insurance– Fraud Detection

Application Selection

• Non-Technical Criteria– Potential benefits and payoffs– Management support– Domain expert– End user interest and involvement– Potential for privacy/legal issues

Application Selection

• Technical Criteria– Sufficient amount of data– High quality data– Prior Knowledge

Current Issues

• Integration– DM with OLAP

• Limited power of commercial DM Tools

• Data quality problem

• Multimedia data: video, audio, images, etc.

• Scaling-up problem