DATA MINING FULL SUMMARY AND REVIEW PLUS QUESTION AND ANSWERS. GUARANTEED A+

DATA MINING 01 INTRODUCTION • Definition • Importance of data mining • Application areas of data mining Business Analytics is a Part of Our Lives • Businesses apply analytics in many different ways to uncover infor ...

DATA MINING 01 INTRODUCTION • Definition • Importance of data mining • Application areas of data mining Business Analytics is a Part of Our Lives • Businesses apply analytics in many different ways to uncover information and to respond to that information appropriately. • Analytics are used to: – Make better medical diagnoses – Lower crime rates – Create effective marketing programs – Improve service availability Objective • Predict the behaviour of future cases, given the past: – build a model on historical data – Apply that model to future cases • Partition your data into: – Training data set – Test data • Business case – Scenario – a bank needs to reduce the risk that a loan is not paid – Approach – use historical data to build a model for risk(high risk customers). – Apply the model to customers or prospects who apply for a loan Why data mining • Living in data rich but information poor situation. • Information age: terabytes and petabytes of data available • How do we consume this data translate it into information and make it usable • important decisions are often made based not on the information-rich data stored in data repositories but rather on a decision maker’s intuition, simply because the decision maker does not have the tools to extract the valuable knowledge embedded in the vast amounts of data. Definition of data mining • Is the process of extracting valid, previously unknown, comprehensible, and actionable information from large databases and using it to make crucial business decisions. • It is the process of discovering insights, patterns and relationship from large amounts of data • Is a knowledge discovery process of automated extraction of hidden predictive information from large databases.