Chat with AIExam 4: Data Mining Process, Methods, and Algorithms
List five reasons for the growing popularity of data mining in the business world.
(30) 
Verified• More intense competition at the global scale driven by customers' ever-changing needs and wants in an increasingly saturated marketplace
• General recognition of the untapped value hidden in large data sources
• Consolidation and integration of database records, which enables a single view of customers, vendors, transactions, etc.
• Consolidation of databases and other data repositories into a single location in the form of a data warehouse
• The exponential increase in data processing and storage technologies
• Significant reduction in the cost of hardware and software for data storage and processing
• Movement toward the de-massification (conversion of information resources into nonphysical form) of business practices
In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing?
(31) VerifiedIf you look at this practice from a legal perspective, you would conclude that Target did not use any information that violates customer privacy; rather, they used transactional data that most every other retail chain is collecting and storing (and perhaps analyzing) about their customers. What was disturbing in this scenario was perhaps the targeted concept: pregnancy. There are certain events or concepts that should be off limits or treated extremely cautiously, such as terminal disease, divorce, and bankruptcy.
In the cancer research case study, data mining algorithms that predict cancer survivability with high predictive power are good replacements for medical professionals.
(39) VerifiedFalse
Decision trees are most appropriate for categorical data and interval data.
(32) The entire focus of the predictive analytics system in the Visa case was on detecting and handling fraudulent charges for the company's benefit.
(34) Describe the difference between quantitative and qualitative data. Include definitions for nominal and ordinal data.
(39) Briefly describe five techniques (or algorithms) that are used for classification modeling.
(37) List and briefly describe the six steps of the CRISP-DM data mining process.
(33) Which index has been used in economics to measure the diversity of a population?
(32) In the Miami-Dade Police Department case, the department chose to start small and grow big in order to demonstrate success with data mining.
(31) ________ data have finite nonordered values (e.g., gender data, which have two values: male and female).
(33) Market basket analysis is a useful and entertaining way to explain data mining to a technologically less savvy audience, but it has little business significance.
(27) Using data mining on data about imports and exports can help to detect tax avoidance and money laundering.
(40) In the terrorist funding case study, predictive analytics helped to identify abnormal transfer prices on exports.
(36) ________ is the splitting mechanism used in ID3, which is perhaps the most widely known decision tree algorithm.
(38) 
Filters
- Essay(0)
- Multiple Choice(0)
- Short Answer(0)
- True False(0)
- Matching(0)