A. For each of the following meetings explain which phase in CRISP-DM process is represented: a. Managers want to know by next week whether deployment will take place. Therefore analysts meet to discuss how useful and accurate their model is. This is the Evaluation phase in the CRISP-DM process. In the evaluation phase the data mining analysts determine if the model and technique used meets business objectives established in the first phase.

B. The data mining project manager meets with the data warehousing manager to discuss how the data will be collected. This is the Data Understanding phase in the CRISP-DM process. The data warehouse is identified as a resource during the Business Understanding phase; however the actual data collection takes place during the Data Understanding Phase. In this phase data is collected and accessed from the resources listed and identified in the Business Understanding phase.

C. The data mining consultant meets with the vice president for marketing, who says that he would like to move forward with the customer relationship management. The main objective of business is to review during the Business Understanding Phase. So, therefore after the meeting it seems the data mining consultant gained success in convincing VP of marketing to provide approval for performing data mining on the customer relationship management system.

D. The data mining project manager meets with the production line supervisor to discuss the implementation of changes and improvements. The discussion of implementation of changes and improvements in the project whether specific improvements or process changes are required to ensure that all important aspects of the business are accounted is performed under the Evaluation Phase. The meeting held with business objective to collect and cleanse the data to ensure the quality of data.

E. The analysts meet to discuss whether the neural network or decision tree models should be applied. This meeting represents the Modeling phase of the CRISP-DM process. In this process after the collected raw data has been cleaned the analysts need to decide which modeling technique should be applied. In the above meeting too the analysts discuss whether they should use the neural network or decision tree model. They need to choose a model that takes into account the business objectives and sometimes two models can be used to see if they confluence at any point.