Data Mining: Data Mining: Software Helping Software Helping Business RunBusiness Run

Group 4Group 4

Austin Beam, Brittany Dearien, Austin Beam, Brittany Dearien, Warren Irwin, Amanda Medlin, Rob Warren Irwin, Amanda Medlin, Rob WestermanWesterman

IntroductionIntroduction

Data Mining definedData Mining defined Basic FactsBasic Facts Goals of data miningGoals of data mining Steps to data miningSteps to data mining What data mining can doWhat data mining can do Data mining in businessData mining in business Advantages/DisadvantagesAdvantages/Disadvantages Data Mining SoftwareData Mining Software Data Mining in the futureData Mining in the future

Data MiningData Mining

Data mining is defined asData mining is defined as– The science of extracting useful The science of extracting useful

information from large data sets or information from large data sets or databasesdatabases

– Also known as Also known as Knowledge-Discovery Knowledge-Discovery in Databasesin Databases (KDD) (KDD)

Basic FactsBasic Facts

Data mining presents information Data mining presents information that would not be available that would not be available otherwiseotherwise

The more data the better!The more data the better!

Must have good data or the Must have good data or the solutions are irrelevantsolutions are irrelevant

Goals of Data MiningGoals of Data Mining

Simplification and automation of the Simplification and automation of the overall statistical process from data overall statistical process from data sources to model application sources to model application

This means:This means:– The The automatedautomated extraction of extraction of hidden hidden

predictivepredictive information from large information from large databasesdatabases

AutomatedAutomated Hidden Hidden PredictivePredictive

Steps to Data MiningSteps to Data Mining

Data mining relieves the pressure Data mining relieves the pressure and need for as many statisticiansand need for as many statisticians

• Begin with a Predictive Model: Begin with a Predictive Model: take various information such as take various information such as family, age, income to answer a family, age, income to answer a questionquestion

• Mathematical Algorithms Mathematical Algorithms

How the data is scoredHow the data is scored– The way data is received/recordedThe way data is received/recorded

Qualitative viewQualitative view:: – provides insight into the data you provides insight into the data you

are working with, but requires are working with, but requires interaction capabilities and good interaction capabilities and good visualizationvisualization

Quantitative viewQuantitative view:: – more of an automated process and more of an automated process and

a bottom line orientationa bottom line orientation

Decision TreesDecision Trees– A series of ‘if/then’ questions that A series of ‘if/then’ questions that

reach a final solutionreach a final solution

Convergence of 3 TechnologiesConvergence of 3 Technologies

Increased Computing

Power

Improved Data Collection

and Management

Statistical Algorithms

DM

What can Data Mining What can Data Mining do?do?

Other than help find new Other than help find new information, data mining can information, data mining can assist in assist in – Finding new patternsFinding new patterns– Recognizing significant factsRecognizing significant facts– Valuing customer loyaltyValuing customer loyalty– Following new and changing trendsFollowing new and changing trends

Data Mining in Data Mining in BusinessBusiness

Market Market segmentation segmentation

Customer churnCustomer churn Fraud detectionFraud detection Direct marketing Direct marketing Interactive Interactive

marketing marketing Market basket Market basket

analysis analysis Trend analysisTrend analysis

Advantages of Data Advantages of Data MiningMining

Automated predictions of trends Automated predictions of trends and behaviorsand behaviors

Discovery of previously unknown Discovery of previously unknown patternspatterns

More time/cost efficient than More time/cost efficient than statisticiansstatisticians

Competitive advantageCompetitive advantage Increased ProfitabilityIncreased Profitability

Disadvantages of Data Disadvantages of Data MiningMining

Is the data Is the data correct?correct?

Who has the Who has the right to this right to this information?information?

PrivacyPrivacy EthicsEthics

Data Mining SoftwareData Mining Software

SAS SAS – 800 Pound Gorilla in the data analysis space 800 Pound Gorilla in the data analysis space

SPSS SPSS InsightfulInsightful (formerly Mathsoft/S-Plus) (formerly Mathsoft/S-Plus)

– Well respected statistical tools, now moving into mining Well respected statistical tools, now moving into mining OracleOracle

– Integrated data mining into the database Integrated data mining into the database Angoss Angoss

– One of the first data mining applications (as opposed to One of the first data mining applications (as opposed to tools) tools)

HNC HNC – Very specific analytic solutions Very specific analytic solutions

Unica Unica – Great mining technology, focusing less on analytics these Great mining technology, focusing less on analytics these

daysdays

Data Mining in the Data Mining in the FutureFuture

Growing TrendsGrowing Trends Data Mining market size of Data Mining market size of

software has grown from $540M software has grown from $540M in 2002, $1.5B in 2005in 2002, $1.5B in 2005

Endless possibilities for everyday Endless possibilities for everyday life!life!