For example, your primary goal might be to keep current customers by predicting when they are prone to move to a competitor. There may also be other related questions that you would like to address. Set objectives – This means describing your primary objective from a business perspective.What are the desired outputs of the project? Neglecting this step can mean that a great deal of effort is put into producing the right answers to the wrong questions. The goal of this stage of the process is to uncover important factors that could influence the outcome of the project. Your organisation may have competing objectives and constraints that must be properly balanced. The first stage of the CRISP-DM process is to understand what you want to accomplish from a business perspective. STAGE ONE – DETERMINE BUSINESS OBJECTIVES You can download our free guide to using CRISP DM to evaluate data mining tools or you can watch the recording of our introduction to CRISP DM webinar. We have other CRISP DM resource available to help you with your data mining projects. You can jump to more information about each phase of the process here: The model does not try to capture all possible routes through the data mining process. In practice many of the tasks can be performed in a different order and it will often be necessary to backtrack to previous tasks and repeat certain actions. This model is an idealised sequence of events. The CRISP-DM model is shown on the right. It is the golden thread than runs through almost every client engagement. We are however evangelists of its powerful practicality, its flexibility and its usefulness when using analytics to solve thorny business issues. It is a robust and well-proven methodology. The CRISP-DM methodology provides a structured approach to planning a data mining project. CRISP-DM stands for cross-industry process for data mining.
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