Data warehouse
Q1. Discuss various types of concept hierarchies by providing two examples for each type?
Q2. Illustrate the typical requirements of clustering data mining.
Q3. State various evaluation criteria that are essential for classification and prediction methods.
Q4. What is meant by data reduction? Discuss any two data reduction strategies for obtaining a reduced data representation.
Q5. Differentiate between STAR and SNOWFLAKE schemas.
Q6. State the salient differences between data query and knowledge query?
Case Study
Q2. Give an example to show that items in a strong association rule may actually be negatively correlated.
Q3. What are Bayesian classifiers? Explain the theorem on which Bayesian classification is based.
Q4. Explain the application of data mining in CRM in Healthcare. How Data Mining algorithms can be implemented in CRM.
1) Which of the following statements correctly describe a Dimension table in Dimensional Modeling?
2) How are dimensions in a Multi-Dimensional Database related?
3) What is a primary risk of a 'phased' implementation?
4) How do highly distributed source systems impact the Data Warehouse or Data Mart project?
5) OLAP tool (as described above)?
6) In a Data Mart Only architecture, what will the Data Mart Development Team(s) encounter?
7) What is the primary responsibility of the 'project sponsor' during a Data Warehouse project?
8) What are Metadata?
9) How can the managers of a department best understand the cost of their use of the data warehouse?
10) Which of the following is NOT a consequence of the creation of independent Data Marts?
11) What is meant by artificial intelligence when it is applied to data cleansing and transformation tools?
12) Which of the following classes of corporations can gain the most insights from their legacy data?
13) Which of the following is NOT found in an Entity Relationship Model?
14) What is Data Mining?
15) What does implementing a Data Warehouse or Data Mart help reduce?
16) Profitability Analysis is one of the most common applications of data warehousing. Why is Profitability Analysis in data warehousing more difficult than usually expected?
17) An operational system is which of the following?
18) A data warehouse is which of the following?
19) The load and index is which of the following?
20) The extract process is which of the following?
21) A star schema has what type of relationship between a dimension and fact table?
22) What does the term 'Ad-hoc Analysis' mean?
23) What should be the business analyst's involvement in monitoring the performance of a
24) What factor heavily influences data warehouse size estimates?
25) What is the advantage of using a WEB interface over a client/server approach?
26). Transient data is which of the following?
27). A multifield transformation does which of the following?
28). A snowflake schema is which of the following types of tables?
29). The generic two-level data warehouse architecture includes which of the following?
30). Fact tables are which of the following?
31) Data transformation includes which of the following?
32. Information is
33) Data by itself is not useful unless
34) What are the three essential components of a learning system
35) The error function most suited for gradient descent using logistic regression is
36) After SVM learning, each Lagrange multiplier ai takes either zero or non-zero value. What does it indicate in each situation?
37) A “Bayesian Network” is most accurately described as
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University: AMITY Year: 2015