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1. Describe four data mining applications is retailing and logistics.(answer in ch5-slide11) 1- Optimize inventory levels at different locations 2- Improve the store layout and sales promotions 3- Optimize logistics by predicting seasonal effects 4-Minimize losses due to limited shelf life

2. List the six steps in a CRISP-DM (Cross-Industry Standard Process for Data Mining). (answer in ch5-slide16) Step 1: Business Understanding
Step 2: Data Understanding
Step 3: Data Preparation (!)
Step 4: Model Building
Step 5: Testing and Evaluation
Step 6: Deployment
The first three steps are Accounts for ~85% of total project time

3. List four ways that cluster analysis for data mining can be used in.(answer in ch5-slide26) Clustering results may be used to:
1- Identify natural groupings of customers 2- Identify rules for assigning new cases to classes for targeting/diagnostic purposes 3- Provide characterization, definition, labeling of populations 4- Decrease the size and complexity of problems for other data mining methods 5- Identify outliers in a specific domain (e.g., rare-event detection)

4. List four data mining myths.(answer in ch5-slide38)
1-provides instant solutions/predictions
2- Is not yet viable for business applications 3- Requires a separate, dedicated database
4- Can only be done by those with advanced degrees 5- Is only for large firms that have lots of customer data 6- Is another name for the good-old statistics 5. What is a data mart? What is the difference between dependent and independent data marts? (answer in ch8-slide6) What is...
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