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FINAL TEST MGT300 INFORMATION TECHNOLOGY IN BUSINESS

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FINAL TEST MGT300 INFORMATION TECHNOLOGY IN BUSINESS
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42 questions

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1.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

Which of the following

represents the different information levels?

Detail, summary, aggregate

Individual, department, enterprise

Document, presentation, spreadsheet, database

Individual, document, presentation, spreadsheet, database

2.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

What is one of the biggest pitfalls associated with real-time information?

It is only available to high-level executives due to the expense

It is only available in aggregate levels of granularity

It continually changes

It rarely changes

3.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

Which of the following database structures stores information in a tree-like structure that allows repeating information using parent/child relationships, in such a way that it cannot have too many relationships?

Hybrid database

Network database

Hierarchical database

Relational database model

4.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

In the relational database model, what is a person, place, thing, transaction, or event about which information is stored?

Entity

Attribute

Constraint

Relationships

5.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

Which of the following is incorrect in reference to a database?

Can be relational or network

Information is accessed by logical structure

Information is accessed by physical structure

Users can access different views of information

6.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

A data warehouse is a __________ collection of information-gathered from many different __________ databases-that supports business analysis activities and decision-making tasks.

Physical, transactional

Physical, operational

Logical, transactional

Logical, operational

7.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

What is data mining?

A particular attribute of information

The common term for the representation of multidimensional information

Process of analyzing data to extract information not offered by the raw data alone

Uses a variety of techniques to find patterns and relationships in large volumes of information and infer rules from them that predict future behavior and guide decision making

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