Large Scale Analysis of Messy Data: Analysis of Programming Practices

Businesses today are trying to economize their practices to increase efficiencies and profits in a highly competitive society. One way a business could do this would be to make a graph of productivity of workers vs. length of work shift. The graph may show that a certain length of work shift may show a greater productivity rate than other shifts. By doing this, the business can decide to reduce the workload or increase the workload to increase productivity, and possibly increase company profits. However, with so many factors and variables, its simple plot may not provide enough information to make such a decision. There are several methods of analysis that can assist the decision-maker in determining a course of action. The following paper deals with software cost estimation, which contains 26 variables that deal with computer programming. Cluster analysis and Factor analysis are introduced to help make interpretations and correlation within the variables. Large Scale Analysis of Messy Data: Analysis of Programming Practice