Data Mining: Software Helping Business Run

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Data Mining Software Helping Business Run

• Group 4
• Austin Beam, Brittany Dearien, Warren Irwin,
  Amanda Medlin, Rob Westerman

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Introduction

• Data Mining defined
• Basic Facts
• Goals of data mining
• Steps to data mining
• What data mining can do
• Data mining in business
• Advantages/Disadvantages
• Data Mining Software
• Data Mining in the future

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Data Mining

• Data mining is defined as
• The science of extracting useful information from
  large data sets or databases
• Also known as Knowledge-Discovery in Databases
  (KDD)

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Basic Facts

• Data mining presents information that would not
  be available otherwise
• The more data the better!
• Must have good data or the solutions are
  irrelevant

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Goals of Data Mining

• Simplification and automation of the overall
  statistical process from data sources to model
  application
• This means
• The automated extraction of hidden predictive
  information from large databases
• Automated Hidden Predictive

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Steps to Data Mining

• Data mining relieves the pressure and need for as
  many statisticians
• Begin with a Predictive Model take various
  information such as family, age, income to answer
  a question
• Mathematical Algorithms

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• How the data is scored
• The way data is received/recorded
• Qualitative view
• provides insight into the data you are working
  with, but requires interaction capabilities and
  good visualization
• Quantitative view
• more of an automated process and a bottom line
  orientation

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• Decision Trees
• A series of if/then questions that reach a
  final solution

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• Convergence of 3 Technologies

DM
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What can Data Mining do?

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

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Data Mining in Business

• Market segmentation
• Customer churn
• Fraud detection
• Direct marketing
• Interactive marketing
• Market basket analysis
• Trend analysis

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Advantages of Data Mining

• Automated predictions of trends and behaviors
• Discovery of previously unknown patterns
• More time/cost efficient than statisticians
• Competitive advantage
• Increased Profitability

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Disadvantages of Data Mining

• Is the data correct?
• Who has the right to this information?
• Privacy
• Ethics

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Data Mining Software

• SAS
• 800 Pound Gorilla in the data analysis space
• SPSS
• Insightful (formerly Mathsoft/S-Plus)
• Well respected statistical tools, now moving into
  mining
• Oracle
• Integrated data mining into the database
• Angoss
• One of the first data mining applications (as
  opposed to tools)
• HNC
• Very specific analytic solutions
• Unica
• Great mining technology, focusing less on
  analytics these days

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Data Mining in the Future

• Growing Trends
• Data Mining market size of software has grown
  from 540M in 2002, 1.5B in 2005
• Endless possibilities for everyday life!