Database Modern Management, Ninth Edition
9
Chapter 12 Data Quality and Integration
MULTIPLE CHOICE: Choose the one alternative that best completes the statement
or answers the question.
1.
High quality data are data that are
A)
Accurate
B)
Consistent
C)
Available in a timely fashion
D)
All of the above
Answer: D
Level: Easy
Page Ref: 524
Topic: Managing Quality Data
AACSB Use of Information Technology, Analytic Skills
2.
A)
B)
C)
D)
Data quality ROI stands for:
Return on investment
Risk of incarceration
Rough outline inclusion
None of the above
Answer: B
Level: Easy
Page Ref: 524
Topic: Managing Quality Data
AACSB Use of Information Technology, Analytic Skills
3.
A)
B)
C)
D)
Data quality is important for all of the following reasons except:
It minimizes project delay
It aids in making timely business decisions
It provides a stream of profit
It helps to expand the customer base
Answer: C
Level: Moderate
Page Ref: 524
Topic: Managing Quality Data
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
10
Data Quality and Integration
4.
A)
B)
C)
D)
Chapter 12
Quality data can be defined as being:
Unique
Inaccurate
Historical
Precise
Answer: A
Level: Easy
Page Ref: 524-525
Topic: Managing Quality Data
AACSB Use of Information Technology
5.
A)
B)
C)
D)
Conformance means that
Data have been transformed
Data are stored, exchanged or presented in a format that is specified by its metadata.
Data are stored in a way to expedite retrieval.
None of the above.
Answer: B
Level: Easy
Page Ref: 525
Topic: Managing Quality Data
AACSB Use of Information Technology
6.
A)
B)
C)
D)
One characteristic of quality data which pertains to the expectation for the time between
when data are expected and when they are available for use is:
Currency
Consistency
Referential Integrity
Timeliness
Answer: D
Level: Easy
Page Ref: 525
Topic: Managing Quality Data
AACSB Use of Information Technology
7.
A)
B)
C)
D)
Experts estimate that ________________ data warehousing projects fail because users
reject the data as unreliable.
All
Half of
No
Seventy percent of
Answer: D
Level: Easy
Page Ref: 526
Topic: Managing Quality Data
Sub-Topic: The State of Data Quality
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
8.
A)
B)
C)
D)
External data sources present problems for data quality because:
Data are not always available.
There is a lack of control over data quality
There are poor data capture controls.
Data are unformatted.
Answer: B
Level: Easy
Page Ref: 526
Topic: Managing Quality Data
Sub-topic: The State of Data Quality
AACSB Use of Information Technology
9.
A)
B)
C)
D)
Data quality problems can cascade when
Data are not deleted properly.
Data are copied from legacy systems.
There is redundant data storage and inconsistent metadata.
There are data entry problems.
Answer: B
Level: Easy
Page Ref: 527
Topic: Managing Quality Data
Sub-Topic: Redundant data storage and inconsistent metadata.
AACSB Use of Information Technology
10.
The best place to improve data entry across all applications is:
A) In the users
B) In the level of organizational commitment
C) In the database definitions
D) In the data entry operators
Answer: C
Level: Easy
Page Ref: 527
Topic: Managing Quality Data
Sub-Topic: Data Entry
AACSB Use of Information Technology
11.
A)
B)
C)
D)
Which of the following are key steps in a data quality program?
Conduct a data quality audit
Apply TQM principles and practices
Estimate return on investment
All of the above.
Answer: D
Level: Moderate
Page Ref: 528
Topic: Managing Quality Data
Sub-Topic: Data Quality Improvement
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
11
12
Data Quality and Integration
12.
A)
B)
C)
D)
Chapter 12
One simple task of a data quality audit is to:
Interview all users
Statistically profile all files
Load all data into a data warehouse
Establish quality metrics.
Answer: B
Level: Moderate
Page Ref: 527
Topic: Managing Quality Data
Sub-Topic: Data Quality Improvement
AACSB Use of Information Technology
13.
A)
B)
C)
D)
One way to improve the data capture process is to:
Allow all data to be entered manually
Provide little or no training to data entry operators
Check entered data immediately for quality against data in the database
Not use any automatic data entry routines
Answer: C
Level: Easy
Page Ref: 529
Topic: Managing Quality Data
Sub-Topic: Data Quality Improvement
AACSB Use of Information Technology
14. A person assigned the responsibility of ensuring data quality in the organization is called
a(n):
A) Data steward
B) Data manager
C) Database administrator
D) Business analyst
Answer: C
Level: Easy
Page Ref: 530
Topic: Managing Quality Data
Sub-Topic: Data Quality Improvement
AACSB Use of Information Technology
15.
A)
B)
C)
D)
Data governance can be defined as:
A means to slow down the speed of data.
High-level organizational groups and processes that oversee data stewardship.
A government task force for defining data quality.
None of the above.
Answer: B
Level: Easy
Page Ref: 530
Topic: Managing Quality Data
Sub-Topic: Data Quality Improvement
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
16.
A)
B)
C)
D)
TQM stands for:
Thomas Quinn Mann, a famous data quality innovator
Total Quality Manipulation
Transforming Quality Management
Total Quality Management
Answer: D
Level: Easy
Page Ref: 531
Topic: Managing Quality Data
Sub-Topic: Data Quality Improvement
AACSB Use of Information Technology
17.
A)
B)
C)
D)
When creating a sound data model, entity types should represent and be named after:
The role that the entity plays in a context
The underlying object
Random events
Actors
Answer: B
Level: Easy
Page Ref: 532
Topic: Managing Quality Data
Sub-Topic: Data Quality Improvement
AACSB Use of Information Technology
18.
A)
B)
C)
D)
All of the following are ways to consolidate data except:
Application integration
Data rollup and integration
Business process integration
User interaction integration
Answer: B
Level: Easy
Page Ref: 533-534
Topic: Data Integration: An Overview
Sub-Topic: General Approaches to Data Integration
AACSB Use of Information Technology
19.
A)
B)
C)
Data federation is a technique which:
Creates an integrated database from several separate databases.
Creates a distributed database
Provides a virtual view of integrated data without actually creating one centralized
database.
D) Provides a real-time update of shared data.
Answer: C
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
Sub-Topic: Data Federation
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
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14
20.
A)
B)
C)
D)
Data Quality and Integration
Chapter 12
_________________ duplicates data across databases.
Data propagation
Data duplication
Redundant replication
A replication server
Answer: A
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
Sub-Topic: Data Propagation
AACSB Use of Information Technology
21.
A)
B)
C)
D)
Event-drive propagation
Provides a means to duplicate data for events
Pushes data to duplicate sites as an event occurs
Pulls duplicate data from redundant sites
None of the above.
Answer: B
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
Sub-Topic: Data Propagation
AACSB Use of Information Technology
22.
A)
B)
C)
D)
The major advantage of data propagation is:
Real-time cascading of data changes throughout the organization.
Duplication of non-redundant data
The ability to have trickle-feeds
None of the above
Answer: A
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
Sub-Topic: Data Propagation
AACSB Use of Information Technology
23.
A)
B)
C)
D)
The methods to ensure the quality of data across various subject areas are called:
Variable Data Management
Master Data Management
Joint Data Management
Managed Data Management
Answer: B
Level: Easy
Page Ref: 535
Topic: Data Integration: An Overview
Sub-Topic: Master Data Management
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
24.
A)
B)
C)
D)
15
All of the following are popular architectures for Master Data Management except::
Identity Registry
Integration Hub
Persistent Object
Normalization
Answer: D
Level: Moderate
Page Ref: 536
Topic: Data Integration: An Overview
Sub-Topic: Master Data Management
AACSB Use of Information Technology
25. In the ________________ approach, one consolidated record is maintained and all
applications draw on that one actual "golden" record.
A) Persistent
B) Identity Registry
C) Federated
D) Integration Hub
Answer: C
Level: Moderate
Page Ref: 536
Topic: Data Integration: An Overview
Sub-Topic: Master Data Management
AACSB Use of Information Technology
26.
A)
B)
C)
D)
A characteristic of reconciled data that means the data reflect an enterprisewide view is:
detailed.
historical.
normalized.
comprehensive.
Answer: D
Level: Moderate
Page Ref: 538
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: Characteristics of Data after ETL
AACSB Use of Information Technology
27.
Informational and operational data differ in all of the following ways EXCEPT:
A)
level of detail.
B)
normalization level.
C)
scope of data.
D)
data quality.
Answer: A
Level: Moderate
Page Ref: 58
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: Characteristics of Data after ETL
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
16
Data Quality and Integration
Chapter 12
28. A method of capturing only the changes that have occurred in the source data since the
last capture is called _____ extract.
A) static
B) incremental
C) partial
D) update-driven
Answer: B
Level: Easy
Page Ref: 540
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
29. A method of capturing only the changes that have occurred in the source data since the
last capture is called _____ extract.
A) static
B) incremental
C) partial
D) update-driven
Answer: B
Level: Easy
Page Ref: 540
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
30.
A)
B)
C)
D)
A technique using artificial intelligence to upgrade the quality of raw data is called:
dumping.
data reconciliation.
completion backwards updates.
data scrubbing.
Answer: D
Level: Easy
Page Ref: 542
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
31.
A)
B)
C)
D)
All of the following are tasks of data cleansing EXCEPT:
decoding data to make them understandable for data warehousing applications.
adding time stamps to distinguish values for the same attribute over time.
generating primary keys for each row of a table.
creating foreign keys.
Answer: D
Level: Moderate
Page Ref:542
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
32. An approach to filling a data warehouse that employs bulk rewriting of the target data
periodically is called:
A) dump mode.
B) overwrite mode.
C) refresh mode.
D) update mode.
Answer: C
Level: Easy
Page Ref: 543
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
33.
A)
B)
C)
D)
Which type of index is commonly used in data warehousing environments?
Join index
Bit-mapped index
Secondary index
Both A and B
Answer: D
Level: Moderate
Page Ref: 543
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
34.
A)
B)
C)
D)
Loading data into a data warehouse involves:
appending new rows to the tables in the warehouse.
updating existing rows with new data.
purging data that have become obsolete or were incorrectly loaded.
all of the above.
Answer: D
Level: Moderate
Page Ref: 543-544
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
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18
Data Quality and Integration
Chapter 12
35.
A)
B)
C)
D)
Data may be loaded from the staging area into the warehouse by following:
SQL Commands (Insert/Update)
Special load utilities
Custom-written routines
All of the above
36.
A)
B)
C)
D)
Answer: D
Level: Moderate
Page Ref: 544
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
The process of combining data from various sources into a single table or view is called:
extracting.
updating.
selecting.
joining.
37.
A)
B)
C)
D)
Answer: D
Level: Easy
Page Ref: 545
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
The process of transforming data from a detailed to a summary level is called:
extracting.
updating.
joining.
aggregating.
Answer: D
Level: Easy
Page Ref: 546
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
38.
A)
B)
C)
D)
Which of the following is a basic method for single field transformation?
Table lookup
Cross-linking entities
Cross-linking attributes
Field-to-field communication
Answer: A
Level: Moderate
Page Ref: 546
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
TRUE/FALSE: Write T if the statement is true and F if the statement is false.
39.
Quality data are not essential for well-run organizations.
Answer: FALSE
Level: Easy
Page Ref: 522
Topic: Introduction
AACSB Use of Information Technology
40.
ETL is short for Extract, Tranform, Load.
Answer: TRUE
Level: Easy
Page Ref: 523
Topic: Introduction
AACSB Use of Information Technology
41.
There are six major steps to ETL.
Answer: FALSE
Level: Easy
Page Ref: 523
Topic: Introduction
AACSB Use of Information Technology
42.
Dirty data saves work for information systems projects.
Answer: FALSE
Level: Easy
Page Ref: 524
Topic: Managing Data Quality
AACSB Use of Information Technology
43.
Data quality is essential for SOX and Basel II compliance.
Answer: TRUE
Level: Easy
Page Ref: 524
Topic: Managing Quality
AACSB Data Use of Information Technology
44.
Quality data does not have to be unique.
Answer: FALSE
Level: Easy
Page Ref: 524
Topic: Managing Data Quality
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
19
20
Data Quality and Integration
Chapter 12
45.
Completeness means that all data that are needed are present.
Answer: TRUE
Level: Easy
Page Ref: 525
Topic: Managing Data Quality
AACSB Use of Information Technology
46.
Retention refers to the amount of data that is not purges periodically from tables.
Answer: FALSE
Level: Easy
Page Ref: 525
Topic: Managing Data Quality
AACSB Use of Information Technology
47.
Bad data can cost a business between 10 and 20 percent of its revenue.
Answer: TRUE
Level: Moderate
Page Ref: 526
Topic: Managing Data Quality
Sub-topic: The State of Quality data
AACSB Use of Information Technology
48.
Generally, records in a customer file never become obsolete.
Answer: FALSE
Level: Moderate
Page Ref: 526
Topic: Managing Data Quality
Sub-topic: The State of Quality data
AACSB Use of Information Technology
49.
Data which arrive via XML and B2B channels is always guaranteed to be accurate.
Answer: FALSE
Level: Moderate
Page Ref: 527
Topic: Managing Data Quality
Sub-topic: External Data Sources
AACSB Use of Information Technology
50. The uncontrolled proliferation of spreadsheets, databases and repositories leads to data
quality problems.
Answer: TRUE
Level: Moderate
Page Ref: 527
Topic: Managing Data Quality
Sub-topic: External Data Sources
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
21
51. A data quality audit helps an organization understand the extent and nature of data quality
problems.
Answer: TRUE
Level: Easy
Page Ref: 528
Topic: Managing Data Quality
Sub-topic: Data Quality Improvement
AACSB Use of Information Technology
52.
A data stewardship program does not help to involve the organization in data quality.
Answer: FALSE
Level: Easy
Page Ref: 528
Topic: Managing Data Quality
Sub-topic: Data Quality Improvement
AACSB Use of Information Technology
53.
Improving the data capture process overcomes the garbage in, garbage out phenomenon.
Answer: TRUE
Level: Easy
Page Ref: 528
Topic: Managing Data Quality
Sub-topic: Data Quality Improvement
AACSB Use of Information Technology
54. A data steward is a person assigned the responsibility of ensuring the organizational
applications properly support the organization's enterprise goals for data quality.
Answer: TRUE
Level: Easy
Page Ref: 530
Topic: Managing Data Quality
Sub-topic: Data Quality Improvement
AACSB Use of Information Technology
55.
A data governance committee is always made up of high-ranking government officials.
Answer: FALSE
Level: Easy
Page Ref: 530
Topic: Managing Data Quality
Sub-topic: Data Quality Improvement
AACSB Use of Information Technology
56.
User interaction integration is achieved by creating fewer user interfaces.
Answer: TRUE
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
Sub-topic: General Approaches to Data Integration
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
22
57.
Data Quality and Integration
Chapter 12
Data federation consolidates all data into one database.
Answer: FALSE
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
Sub-topic: Data Federation
AACSB Use of Information Technology
58. The major advantage of the data propagation approach to data integration is the near realtime cascading of data changes throughout the organization.
Answer: TRUE
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
Sub-topic: Data Propagation
AACSB Use of Information Technology
59. Master data management is the disciplines, technologies and methods to ensure the
currency, meaning and quality of data within one subject area.
Answer: FALSE
Level: Easy
Page Ref: 535
Topic: Data Integration: An Overview
Sub-topic: Master Data Management
AACSB Use of Information Technology
60. The data reconciliation process is responsible for transforming operational data to
reconciled data.
Answer: TRUE
Level: Easy
Page Ref:537
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: Characteristics of Data after ETL
AACSB Use of Information Technology
61. After the extract, transform, and load is done on data, the data warehouse is never fully
normalized.
Answer: FALSE
Level: Easy
Page Ref: 537
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: Characteristics of Data after ETL
AACSB Use of Information Technology
62.
Data reconciliation occurs in two stages, an initial load and subsequent updates.
Answer: TRUE
Level: Moderate
Page Ref: 538
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: Characteristics of Data after ETL
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
23
63. Static extract is a method of capturing only the changes that have occurred in the source
data since the last capture.
Answer: FALSE
Level: Easy
Page Ref: 540
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
64. One of the biggest challenges of the extraction process is managing changes in the source
system.
Answer: TRUE
Level: Difficult
Page Ref: 540
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
65.
Data are moved to the staging area before extraction takes place.
Answer: FALSE
Level: Moderate
Page Ref: 540
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
66. Data scrubbing is a technique using pattern recognition and other artificial intelligence
techniques to upgrade the quality of raw data before transforming and moving the data to the
data warehouse.
Answer: TRUE
Level: Easy
Page Ref: 542
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
67. Total quality management (TQM) focuses on defect correction rather than defect
prevention.
Answer: FALSE
Level: Difficult
Page Ref: 542
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
24
Data Quality and Integration
Chapter 12
68. Refresh mode is an approach to filling the data warehouse that employs bulk rewriting of
the target data at periodic intervals.
Answer: TRUE
Level: Easy
Page Ref: 543
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
69.
Update mode is used to create a data warehouse.
Answer: FALSE
Level: Easy
Page Ref: 543
Topic: The Reconciled Data Layer
Subtopic: The ETL Process
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
70.
Bit-mapped indexing is often used in a data warehouse environment.
Answer: TRUE
Level: Easy
Page Ref: 543
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
71. Loading data into the warehouse typically means appending new rows to tables in the
warehouse as well as updating existing rows with new data.
Answer: TRUE
Level: Easy
Page Ref: 543
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
72.
Data transformation is not an important part of the data reconciliation process.
Answer: FALSE
Level: Easy
Page Ref: 544
Topic: Data Transformation
AACSB Use of Information Technology
73.
Joining is often complicated by problems such as errors in source data.
Answer: TRUE
Level: Moderate
Page Ref:545
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
25
74. The process of transforming data from detailed to summary levels is called
normalization.
Answer: FALSE
Level: Easy
Page Ref: 546
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
75. Data quality tools are used to assess the quality of existing systems and compare them to
the requirements of the data warehouse.
Answer: TRUE
Level: Moderate
Page Ref: 547
Topic: Data Transformation
Subtopic: Tools to Support Data Reconciliation x
AACSB Use of Information Technology
76. Data conversion tools can support data transformation in a data warehousing
environment.
Answer: TRUE
Level: Moderate
Page Ref: 549
Topic: Data Transformation
Subtopic: Tools to Support Data Reconciliation x
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
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Data Quality and Integration
Chapter 12
SHORT ANSWER: Write the word or phrase that best completes each statement or
answers the question.
___________ ______________ can cause delays and extra work on information
systems projects.
Answer: dirty data
Level: Easy
Page Ref: 524
Topic: Managing Data Quality
AACSB Use of Information Technology
77.
78. Completeness means that all data that must have a ______________ does have a
____________.
Answer: value
Level: Easy
Page Ref: 525
Topic: Managing Data Quality
AACSB Use of Information Technology
79. Conformance refers to whether the data is stored, exchanged or presented in a format that
is as specified by its ___________________.
Answer: metadata
Level: Easy
Page Ref: 525
Topic: Managing Data Quality
AACSB Use of Information Technology
80. Experts estimate that up to seventy percent of data warehousing projects fail because
users reject the data as _____________.
Answer: unreliable
Level: Easy
Page Ref: 526
Topic: Managing Data Quality
Subtopic: The State of Quality Data
AACSB Use of Information Technology
81. A(n) _______________ will thoroughly review all process controls on data entry and
maintenance.
Answer: audit
Level: Easy
Page Ref: 528
Topic: Managing Data Quality
Subtopic: The State of Quality Data
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
27
82. Improving _____________ ____________________ ______________ is a fundamental
step in data quality improvement.
Answer: data capture processes
Level: Easy
Page Ref: 529
Topic: Managing Data Quality
Subtopic: The State of Quality Data
AACSB Use of Information Technology
83. A _____________ _______________ is a person assigned the responsibility of ensuring
that organizational applications properly support the organization's enterprise goals of data
quality.
Answer: data steward
Level: Easy
Page Ref: 530
Topic: Managing Data Quality
Subtopic: The State of Quality Data
AACSB Use of Information Technology
84.
Sound data ___________________ is a central ingredient of a data quality program.
Answer: modeling
Level: Easy
Page Ref: 531
Topic: Managing Data Quality
Subtopic: The State of Quality Data
AACSB Use of Information Technology
________________ _____________________ is achieved by coordinating the flow of
event information between business applications.
Answer: application integration
Level: Easy
Page Ref: 533
Topic: Data Integration: An Overview
AACSB Use of Information Technology
85.
86. User interaction integration is achieved by creating fewer ______________
_____________ that feed different systems.
Answer: user interfaces
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
AACSB Use of Information Technology
87. ______________________ _______________________ provides a virtual view of
integrated data without actually bringing the data into one physical database.
Answer: data federation
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
28
88.
Data Quality and Integration
Chapter 12
Data propagation duplicates data across databases, usually with no _________ delay.
Answer: real-time
Level: Easy
Page Ref: 534
Topic: Data Integration: An Overview
AACSB Use of Information Technology
89. In the _______________ approach, one consolidated record is maintained from which all
applications draw data.
Answer: persistent
Level: Easy
Page Ref: 536
Topic: Data Integration: An Overview
AACSB Use of Information Technology
90.
A method of capturing data in a snapshot at a point in time is called _____ extract.
Answer: static
Level: Easy
Page Ref: 540
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
91.
A technique using pattern recognition to upgrade the quality of raw data is called
_____.
Answer: data scrubbing
Level: Easy
Page Ref: 542
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
92.
An approach in which only changes in the source data are written to the data
warehouse is called _____.
Answer: update mode
Level: Easy
Page Ref: 543
Topic: Data Integration for Data Warehousing: The Reconciled Data Layer
Subtopic: The ETL Process
AACSB Use of Information Technology
93.
Converting data from the format of its source to the format of its destination is
called _________ _________.
Answer: data transformation
Level: Easy
Page Ref: 544
Topic: Data Transformation
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall
Modern Database Management, Ninth Edition
94.
29
The process of partitioning data according to predefined criteria is called _____.
Answer: selection
Level: Easy
Page Ref: 545
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
95.
The process of transforming data from a detailed to a summary level is called
__________.
Answer: aggregation
Level: Easy
Page Ref: 546
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
96.
A(n) _________ ___________ function converts data from a given format in a
source record to a different format in a target record.
Answer: field-level
Level: Moderate
Page Ref: 546
Topic: Data Transformation
Subtopic: Data Transformation Functions
AACSB Use of Information Technology
Copyright 2009 Pearson Education, Inc. Publishing as Prentice Hall