Deck 9: Business Intelligence and Information Systems for Decision Making

Question 1

Problematic data are termed as ________.

A) rough data
B) clickstream data
C) granular data
D) dirty data

Answer 1

D

Question 2

[e-mail] is an example of ________.

A) dirty data
B) coarse data
C) inconsistent data
D) fine data

Answer 2

A

Question 3

A petabyte consists of ________ bytes.

A) 10⁹
B) 10¹²
C) 10¹⁵
D) 10¹⁸

Answer 3

C

Question 4

Which of the following systems use If/Then rules?

A) data-mining systems
B) knowledge-management systems
C) expert systems
D) reporting systems

Question 5

Which of the following is a problem commonly associated with operational data that have been gathered over time?

A) too fine
B) nonintegrated
C) inconsistent
D) missing values

Question 6

Decision tree analysis is a technique used by ________ systems.

A) knowledge management
B) data-mining
C) reporting
D) expert

Question 7

A type written page is about 2 ________.

A) megabytes
B) kilobytes
C) terabytes
D) petabytes

Question 8

If Patient_Temperature > 103,Then Initiate High_Fever-Procedure.This sort of a rule is most likely to be found in a(n)________ system.

A) expert
B) knowledge management
C) operational
D) reporting

Question 9

________ compute(s)the correlation of items on past orders to determine items that are frequently purchased together.

A) Market-basket analysis
B) Knowledge management systems
C) Expert systems
D) Clickstream data

Question 10

________ systems improve decision making by using the discovered patterns and relationships to anticipate events or to predict future outcomes.

A) Knowledge management
B) Expert
C) Reporting
D) Data-mining

Question 11

One ________ is equal to 10¹⁸ bytes

A) megabyte
B) gigabyte
C) exabyte
D) terabyte

Question 12

________ refer(s)to the degree of summarization or detail.

A) Data abstraction
B) Data granularity
C) Gross data
D) Data aggregation

Question 13

One ________ is equal to 10³ bytes.

A) petabyte
B) gigabyte
C) megabyte
D) kilobyte

Question 14

How many bytes make up 1 gigabyte?

A) 10⁹
B) 10¹²
C) 10¹⁵
D) 10¹⁸

Question 15

One megabyte is equal to ________ bytes.

A) 1,000
B) 1,000,000,000
C) 1,000,000,000,000
D) 1,000,000

Question 16

Reporting systems improve decision making by ________.

A) providing the right information to the right user at the right time
B) discovering patterns and relationships in data to predict future outcomes
C) fostering innovation and improving customer service
D) encoding, saving, and processing expert knowledge

Question 17

The advantage that ________ have over the other systems is that these foster innovation,improve customer service,increase organizational responsiveness,and reduce costs.

A) reporting systems
B) expert systems
C) data mining systems
D) knowledge management systems

Question 18

________ systems integrate data from multiple sources,and they process that data by sorting,grouping,summing,averaging,and comparing.

A) Knowledge management
B) Data-mining
C) Expert
D) Reporting

Question 19

________ bytes equal one terabyte.

A) 1,000
B) 1,000,000
C) 1,000,000,000,000
D) 1,000,000,000

Question 20

________ is information containing patterns,relationships,and trends.

A) Technical writing
B) Raw data
C) Business intelligence
D) Internal communication

Question 21

The purpose of a ________ is to extract and clean data from operational systems and other sources,and to store and catalog that data for processing by BI tools.

A) data harvester
B) data center
C) data aggregator
D) data warehouse

Question 22

In ________,statistical techniques identify groups of entities that have similar characteristics.

A) cluster analysis
B) neural networks
C) regression analysis
D) curve fitting

Question 23

In unsupervised data mining ________.

A) analysts do not create a model or hypothesis before running the analysis
B) analysts apply statistical techniques to data to estimate parameters of a model
C) analysts use tools such as regression analysis
D) analysts fit data to suggested hypotheses

Question 24

A ________ is a data collection that is created to address the needs of a particular business function,problem,or opportunity.

A) data mart
B) data harvester
C) data mine
D) data warehouse

Question 25

Generally,it is better to have data that is ________ than data that is ________.

A) random; specific
B) inconsistent; unintegrated
C) too fine; too coarse
D) problematic; dirty

Question 26

Clickstream data is ________.

A) inconsistent
B) too coarse
C) too fine
D) dirty data

Question 27

Which of the following data-mining techniques is used to predict values and make classifications,such as "good prospect" or "poor prospect" customers?

A) cluster analysis
B) neural networks
C) market basket analysis
D) regression analysis

Question 28

________ is the application of statistical techniques to find patterns and relationships among data and to classify and predict.

A) Data encryption
B) Data warehousing
C) Data mining
D) Data compression

Question 29

________ are comparable to distributors in a supply chain because they take data from the data manufacturers,clean and process the data,and locate the data on the disks of its computers.

A) Database servers
B) Data marts
C) Data warehouses
D) Data harvesters

Question 30

Regression analysis is used in ________.

A) expert systems
B) knowledge management systems
C) data-mining systems
D) reporting systems

Question 31

________ data is highly summarized.

A) Coarse
B) Missing
C) Clickstream
D) Dirty

Question 32

With ________ data mining,data miners develop a model prior to the analysis and apply statistical techniques to data to estimate parameters of the model.

A) cluster
B) supervised
C) clickstream
D) unsupervised

Question 33

Which term is used as a synonym for data mining?

A) OLAP
B) neural networks
C) market-basket analysis
D) knowledge discovery in databases

Question 34

A ________ is a company that obtains data from public and private sources and stores,combines,and publishes it in sophisticated ways.

A) data aggregator
B) data harvester
C) data center
D) date warehouse

Question 35

The more attributes there are,the easier it is to build a model that fits the sample data but that is worthless as a predictor.Which of the following best explains this phenomenon?

A) the free rider problem
B) the curse of dimensionality
C) the tragedy of the commons
D) the zero-sum game

Question 36

The facts about data,such as its source,format,assumptions,constraints,and the like,are called ________.

A) metadata
B) folksonomies
C) microdata
D) data packets

Question 37

________ measures the impact of a set of variables on another variable.

A) Cluster analysis
B) Neural networking
C) Granularity
D) Regression analysis

Question 38

Which of the following is a common unsupervised data-mining technique?

A) cluster analysis
B) regression analysis
C) neural networking
D) market-basket analysis

Question 39

1,000,000 bytes equal one gigabyte.

Question 40

Which of the following is true for data warehouses?

A) Data are stored in a data warehouse database using a data warehouse DBMS.
B) Data warehouses are prohibited from purchasing data from outside sources.
C) User-generated content applications generate potentially large amounts of data.
D) Purchased data is more accurate than data collected directly from clients.

Question 41

Data warehouses cannot purchase external data from outside resources.

Question 42

A terabyte is larger than a petabyte in terms of computer storage.

Question 43

Expert systems encapsulate the knowledge of human experts in the form of If/Then rules.

Question 44

Raw operational data is seldom suitable for more sophisticated reporting or data mining.

Question 45

Generally,it is better to have data that is too coarse a granularity than data that is too fine.

Question 46

Data from social networking and user-generated content applications are likely be more accurate than purchased data.

Question 47

Data that are critical for successful operations must be complete and accurate,however data that are only marginally necessary do not need to be.

Question 48

One kilobyte consists of 1,000 bytes.

Question 49

Data-mining systems integrate data from multiple sources,processing it by sorting,grouping,and averaging,and delivering reports on the results.

Question 50

Data marts are usually larger than data warehouses.

Question 51

A typical low-resolution photograph is equal to 1 terabyte.

Question 52

Data marts are data collections that address a particular business problem or opportunity.

Question 53

The curse of dimensionality states that the more attributes there are,the more difficult it is to build a model that fits the sample data but the more relevant it is as a predictor.

Question 54

Data warehouses extract and clean data from operational systems.

Question 55

Data granularity refers to the degree of detail of the data.

Question 56

Market-basket analysis is a data mining system.

Question 57

An organization's data warehouse DBMS cannot be different from the organization's operational DBMS.

Question 58

Data warehouses and data marts are expensive to create,staff,and operate.

Question 59

Reporting systems compute correlations of items on past orders in order to determine items that were frequently purchased together.

Question 60

Knowledge-management systems follow If/Then rules.

Question 61

What is the difference between a megabyte and a gigabyte?

Question 62

Cluster analysis and neural networks are examples of supervised data mining techniques.

Question 63

How is a data warehouse different from a data mart?

Question 64

KDD is synonymous with data mining.

Question 65

Cluster analysis measures the impact of one set of variables on another variable.

Question 66

What is a business intelligence system?

Question 67

Write a brief note on the characteristics and advantages of expert system.

Question 68

What is unsupervised data mining?

Question 69

With unsupervised data mining,analysts do not create a model or hypothesis before running the analysis.

Question 70

Explain the characteristics and advantages of data mining systems.

Question 71

What is data granularity?

Question 72

What is the purpose of a data warehouse?

Question 73

Describe the characteristics and advantages of reporting systems.

Question 74

Explain the curse of dimensionality.

Question 75

Regression analysis is used to find groups of similar customers from customer order and demographic data.

Question 76

Explain supervised data-mining and list the techniques used in it.

Question 77

What is dirty data?

Question 78

What are the characteristics and advantages of knowledge management systems?

Question 79

Explain clickstream data.

Question 80

What is data mining?