Q1. This is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions
Q2. This is the processing of data about customers and their relationship with the enterprise in order to improve the enterprise's future sales and service and lower cost
Q3. This is a central point in an enterprise from which all customer contacts are managed
Q4. In an Internet context, this is the practice of tailoring Web pages to individual users' characteristics or preferences
Q5. Which of the following is not a reason that operational data are difficult to read?
Q6. This is an arrangement in which a company outsources some or all of its customer relationship management functions to an application service provider (ASP).
Q7. In OLAP, we are interested in ________
Q8. We have Market Basket data for 1,000 rental transactions at a Video Store. There are four videos for rent -- Video A, Video B, Video C and Video D. The probability that Video D will be rented given that Video C has been rented is known as ________
Q9. This is an XML-based metalanguage developed by the Business Process Management Initiative (BPMI) as a means of modeling business processes, much as XML is, itself, a metalanguage with the ability to model enterprise data
Q10. One popular classification technique in Business Intelligence (BI) reporting is ________
Q11. This is a systematic approach to the gathering, consolidation, and processing of consumer data (both for customers and potential customers) that is maintained in a company's databases
Q12. This is an approach to selling goods and services in which a prospect explicitly agrees in advance to receive marketing information
Q13. We have done an RFM analysis on our customer data. Mary Jones has a score of "1 1 5". This series means that Mary ________
Q14. This is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests, spending habits, and so on
Q15. In data mining, this is a technique used to predict future behavior and anticipate the consequences of change
