Question 1

Which of the following is a limitation of data mining?

Accepted Answer

A)  Identification of missing data 
B)  Data noise 
C)  Missing values 
D)  All of the above. 
A)  Identification of missing data 
B)  Data noise 
C)  Missing values 
D)  All of the above. A

Question 2

A synonym for data mining is information sifting and discovery (ISD).

Accepted Answer

A) True 
 B)False  False

Question 3

MOLAP provides support for concurrent users.

Accepted Answer

A) True 
 B)False  True

Question 4

Data mining is a business solution, not a technology.

Accepted Answer

A) True 
 B)False

Question 5

In _____________, the multidimensional database server is replaced with a large relational database server. This "super" relational database will contain both detailed and summarized data thus allowing for "drill down" techniques to be applied to the data sets.

Accepted Answer

A)  OLAP 
B)  MOLAP 
C)  ROLAP 
D)  None of the above. 
A)  OLAP 
B)  MOLAP 
C)  ROLAP 
D)  None of the above.

Question 6

Which of the following is a reason for the growth in popularity of data mining?

Accepted Answer

A)  Increased volume of data 
B)  Increased awareness of the inadequacy of the human brain to process multifactorial dependencies or correlations 
C)  Increased affordability of machine learning 
D)  All of the above. 
A)  Increased volume of data 
B)  Increased awareness of the inadequacy of the human brain to process multifactorial dependencies or correlations 
C)  Increased affordability of machine learning 
D)  All of the above.

Question 7

Sparcity can significantly increase the storage requirements of a MOLAP hypercube by requiring that space be allocated for all cells rather than just the ones that contain data values.

Accepted Answer

A) True 
 B)False

Question 8

One of the primary reasons for the rise in data mining popularity is the ever-increasing volume of data that require processing.

Accepted Answer

A) True 
 B)False

Question 9

ROLAP databases typically contain both summary and detail data.

Accepted Answer

A) True 
 B)False

Question 10

There are some cases where it is difficult or impossible to define the parameters of a class of data to be analyzed. In these cases, _____________ methods can be used to create partitions so that all members of each set are similar according to some metric or set of metrics thus creating a set of objects grouped together by virtue of their similarity or proximity to each other.

Accepted Answer

A)  association 
B)  linkage analysis 
C)  sequencing 
D)  clustering 
A)  association 
B)  linkage analysis 
C)  sequencing 
D)  clustering

Question 11

The sequencing approach to data mining relates events in time, based on a series of preceding events.

Accepted Answer

A) True 
 B)False

Question 12

The ROLAP structure contains a large number of normalized tables.

Accepted Answer

A) True 
 B)False

Question 13

One of the primary advantages of ROLAP versus MOLAP is it results in performance improvements for data access.

Accepted Answer

A) True 
 B)False

Question 14

The set of activities used to find new, hidden, or unexpected patterns in data is referred to as:

Accepted Answer

A)  data warehousing. 
B)  data mining. 
C)  data transformation. 
D)  data aggregation. 
A)  data warehousing. 
B)  data mining. 
C)  data transformation. 
D)  data aggregation.

Question 15

What are Codd's twelve rules for OLAP?

Accepted Answer

1. Multidimensional view
2. Transparent

Question 16

Which of the following is not an advantage of market basket analysis?

Accepted Answer

A)  Identifying which products sell together can help manage inventory. 
B)  It is more preferable to marketers to market to existing customers. 
C)  Market basket analysis can sometimes produce results that are due to prior marketing campaigns. 
D)  All of the above are advantages. 
A)  Identifying which products sell together can help manage inventory. 
B)  It is more preferable to marketers to market to existing customers. 
C)  Market basket analysis can sometimes produce results that are due to prior marketing campaigns. 
D)  All of the above are advantages.

Question 17

An orderly hierarchy of items and item categories that divides each item into a basket analysis is referred to as a:

Accepted Answer

A)  cluster analysis. 
B)  taxonomy. 
C)  multi dimensional market basket analysis. 
D)  None of the above. 
A)  cluster analysis. 
B)  taxonomy. 
C)  multi dimensional market basket analysis. 
D)  None of the above.

Question 18

Data mining does not use statistical techniques because the complex patterns in data do not lend themselves to linear regression analysis.

Accepted Answer

A) True 
 B)False

Question 19

A common example of the use of association methods where a retailer can mine the data generated by a point-of-sale system, such as the price scanner you are familiar with at the grocery store is referred to as:

Accepted Answer

A)  sequencing. 
B)  linkage analysis. 
C)  clustering. 
D)  market basket analysis. 
A)  sequencing. 
B)  linkage analysis. 
C)  clustering. 
D)  market basket analysis.

Question 20

Two new categories of data mining are text mining and Web mining.

Accepted Answer

A) True 
 B)False

Which of the following is a limitation of data mining?

A synonym for data mining is information sifting and discovery (ISD).

MOLAP provides support for concurrent users.

Data mining is a business solution, not a technology.

In _____________, the multidimensional database server is replaced with a large relational database server. This "super" relational database will contain both detailed and summarized data thus allowing for "drill down" techniques to be applied to the data sets.

Which of the following is a reason for the growth in popularity of data mining?

Sparcity can significantly increase the storage requirements of a MOLAP hypercube by requiring that space be allocated for all cells rather than just the ones that contain data values.

One of the primary reasons for the rise in data mining popularity is the ever-increasing volume of data that require processing.

ROLAP databases typically contain both summary and detail data.

The sequencing approach to data mining relates events in time, based on a series of preceding events.

The ROLAP structure contains a large number of normalized tables.

One of the primary advantages of ROLAP versus MOLAP is it results in performance improvements for data access.

The set of activities used to find new, hidden, or unexpected patterns in data is referred to as:

What are Codd's twelve rules for OLAP?

Which of the following is not an advantage of market basket analysis?

An orderly hierarchy of items and item categories that divides each item into a basket analysis is referred to as a:

Data mining does not use statistical techniques because the complex patterns in data do not lend themselves to linear regression analysis.

A common example of the use of association methods where a retailer can mine the data generated by a point-of-sale system, such as the price scanner you are familiar with at the grocery store is referred to as:

Two new categories of data mining are text mining and Web mining.

Introduction to Decision Support Systems

Decisions and Decision Makers

Decisions in the Organization

Modeling Decision Processes

Group Decision Support and Groupware Technologies

Executive Information Systems

Expert Systems and Artificial Intelligence

Knowledge Engineering and Acquisition

Machines That Can Learn

The Data Warehouse

Designing and Building the Data Warehouse

Decisions in the Organization

Designing and Building Decision Support Systems

Implementing and Integrating Decision Support Systems

Creative Decision Making and Problem Solving

Intelligent Software Agents, Bots, Delegation, and Agency

Decision Support in the Twenty-First Century

Filters

Exam 11: Data Mining and Data Visualization

Which of the following is a limitation of data mining?

A synonym for data mining is information sifting and discovery (ISD).

MOLAP provides support for concurrent users.

Data mining is a business solution, not a technology.

In _____________, the multidimensional database server is replaced with a large relational database server. This "super" relational database will contain both detailed and summarized data thus allowing for "drill down" techniques to be applied to the data sets.

Which of the following is a reason for the growth in popularity of data mining?

Sparcity can significantly increase the storage requirements of a MOLAP hypercube by requiring that space be allocated for all cells rather than just the ones that contain data values.

One of the primary reasons for the rise in data mining popularity is the ever-increasing volume of data that require processing.

ROLAP databases typically contain both summary and detail data.

The sequencing approach to data mining relates events in time, based on a series of preceding events.

The ROLAP structure contains a large number of normalized tables.

One of the primary advantages of ROLAP versus MOLAP is it results in performance improvements for data access.

The set of activities used to find new, hidden, or unexpected patterns in data is referred to as:

What are Codd's twelve rules for OLAP?

Which of the following is not an advantage of market basket analysis?

An orderly hierarchy of items and item categories that divides each item into a basket analysis is referred to as a:

Data mining does not use statistical techniques because the complex patterns in data do not lend themselves to linear regression analysis.

A common example of the use of association methods where a retailer can mine the data generated by a point-of-sale system, such as the price scanner you are familiar with at the grocery store is referred to as:

Two new categories of data mining are text mining and Web mining.

Introduction to Decision Support Systems

Decisions and Decision Makers

Decisions in the Organization

Modeling Decision Processes

Group Decision Support and Groupware Technologies

Executive Information Systems

Expert Systems and Artificial Intelligence

Knowledge Engineering and Acquisition

Machines That Can Learn

The Data Warehouse

Designing and Building the Data Warehouse

Decisions in the Organization

Designing and Building Decision Support Systems

Implementing and Integrating Decision Support Systems

Creative Decision Making and Problem Solving

Intelligent Software Agents, Bots, Delegation, and Agency

Decision Support in the Twenty-First Century

Filters