Computer Science 1032A/B Lecture Notes - Lecture 24: Expert System, Data Warehouse, Intellectual Capital

• School: Western University
• Department: Computer Science
• Course: Computer Science 1032A/B
• Professor: Louis Magguilli

Document Summary

Primary systems: reporting systems, data-mining systems, knowledge management systems, expert systems. Process data: sorting, grouping, summing, averaging, comparing. Improve decision making by providing right information to right user at right time. Process data using statistical techniques: regression analysis, decision tree analysis. Look for patterns and relationships to anticipate events or predict outcomes: market-basket analysis, predict donations. Application of statistical techniques to find patterns and relationships among data. Takes advantage of developments in data management to process enormous databases. Data-mining technique applied and then results are observed. Hypotheses created after analysis to explain the results. Example: cluster analysis: technique to identify groups of entities that have similar characteristics. Statistical techniques used to estimate parameters: examples: Measures impact of a set of variables on another variable. Creates probabilities that two items will be purchased together: customer buying x tends to buy y so when a customer buys either x or y sell them the other product.