CRISP Process Stephen Wyrick

Phase One: Business Understanding Determine the Business Objectives Understanding the client’s true goals Assess the Situation Outline the resources available to accomplish the data mining project The data analyst should: List project risks List potential solutions to those risks Create a glossary of business and data mining terms Construct a cost-benefit analysis for the project

Phase One: Business Understanding Determine the Data Mining Goals State project objectives in business terms Produce a Project Plan This plan describes the intention for achieving the data mining goals This includes: Outlining specific steps and a proposed timeline An assessment of potential risks An initial assessment of the tools and techniques needed to support the project

Phase Two: Data Understanding Collect the Initial Data Acquire necessary data Make sure to report problems encountered and the solutions Describe the Data Examine the properties of the data Report on the results Key question: does the data acquired satisfy the relevant requirements?

Phase Two: Data Understanding Explore the Data Answer the data mining questions Create an exploration report Verify Data Quality Examine the quality of the data

Phase Three: Data Preparation Select Data Decide what data will be included and excluded for the analysis Clean Data Select clean subsets from the data Construct Data After data is cleaned, you should do data preparation operations This includes developing new records or producing derived attributes Integrate Data Combine information from multiple tables or records Format Data Change the format or design of the data if needed

Phase Four: Modeling Select the Modeling Technique Choose the specific modeling technique to use Generate Test Design Separate data into a test and train set Build the model on the train set Estimate its quality on the separate test set Build the Model Create one or more models by running the modeling tool Assess the Model Interpret the models Rank the models

Phase Five: Evaluation Evaluate Results Assess the degree to which the model meets the business objectives Determine if there is some business reason why this model is deficient Summarize the assessment results Review Process A more thorough review of the data mining engagement Covers quality assurance Determine Next Steps Must decide whether to finish this project and move on to deployment or whether to initiate further iterations

Phase Six: Deployment Plan Deployment Plan Monitoring and Maintenance Takes evaluation results and develops a strategy for deployment Plan Monitoring and Maintenance A carefully prepared maintenance strategy avoids incorrect usage of results Produce Final Report Includes previous deliverables and summarizes and organizes the results Review Project Assess failures and successes to help improve future projects