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IBM InfoSphere Warehouse V9.5 Sample Questions:

1. What is meant by "Information as a Service"?

A) extending the traditional data warehouse by providing business context layers to the data
B) expanding a traditional data warehouse with XML capabilities for the data
C) accessing a traditional data warehouse with a Web-based application for the data
D) storing all analytical data in a multidimensional cube instead of a traditional data warehouse

2. You manage a store and want to increase the sales of some high profit items. One way to do this is by placing these items close to other products that are often purchased with the high profit items.
You have a year's history of all sales, including all the items that were purchased in each sale. To determine optimal product placement for the high profit items, which mining method should be used to analyze your data?

A) Clustering
B) Association
C) Regression
D) Classification

3. Using InfoSphere Warehouse Design Studio, which two are required before you can work on a physical data model? (Choose two.)

A) You need to create an ER diagram.
B) You need to identify either the source or the target databases.
C) You need to create a control flow.
D) You need to create a data design project.
E) You need to create a data flow.

4. For recovery purposes, it is desired to keep the output of several data flow operators after the execution has ended. This can be done in two different ways. Which two types of operators and properties would you use to keep the output? (Choose two.)

A) A Data Station operator defined as pass through.
B) A Data Station operator with a type of file and a file name.
C) A Data Station operator with a type of view and a view name.
D) A Data Station operator with a type of persistent table and a table name.
E) A Data Station operator with a type of temporary table and a table name.

5. You work for an insurance company and have been asked to help find a way to detect which health care providers may be submitting fraudulent claims. Which mining method would you employ?

A) sequences
B) regression prediction
C) associations
D) clustering

Solutions: