Data Mining

Data Mining

1. Data Mining

   • Once data has been stored in data warehouse it then needs to be 'mined' to discover...
     • Patterns in the data
     • Associations in the data
     • Trends over time
   • Allows users to understand the data more by descovering meaningful patterns in the data
   • Presents meaningful data results as graphs and tables.
   • Can produce information such as...
     • Lists of customers likely to buy a certain product.
       • Based on what they have baught before.
     • Comparisons with competitors.
     • Useful 'what if' results from modelling exercises
     • Prediction for future sales analysis of best sites for shops.
     • Sales patterns
     • Customer patterns
     • Who is most likely to chnage thier credit card.
     • Customers who are most loyal to company / product.

2. Applications Of Data Mining

   • Helping fight against terrorism
     • Since 9/11, US government has been analysiing peoples travel, spending and communication habbits.
     • Spot patterns of abnormal behaviour that could lead to terrorism
   • Fighting shop lifting
     • With information about transactions and positions of clothes in stores, it is found that most clothes near doors get stolen dispite tags.
     • More money needs to be spend on CCTV and the police.
       • This can gain prosecutions and recover stolen goods.
   • Identification of customer needs.
     • Vegin Media, who supply broadband, telephone and cable TV packages, use data mining
       • Used to segment and target customers likely to buy new servies / upgrade those services they already have.