Review Process

Effective methodologies usually include time for reflection on the successes and weaknesses of the process just completed. Data mining is no different. Part of CRISP-DM is learning from your experience so that future data mining projects will be more effective.

Task List

First, you should summarize the activities and decisions for each phase, including data preparation steps, model building, etc. Then for each phase, consider the following questions and make suggestions for improvement:

• Did this stage contribute to the value of the final results?
• Are there ways to streamline or improve this particular stage or operation?
• What were the failures or mistakes of this phase? How can they be avoided next time?
• Were there dead ends, such as particular models that proved fruitless? Are there ways to predict such dead ends so that efforts can be directed more productively?
• Were there any surprises (both good and bad) during this phase? In hindsight, is there an obvious way to predict such occurences?
• Are there alternative decisions or strategies that might have been used in a given phase? Note such alternatives for future data mining projects.