978-0133546231 Chapter 07 Part 1

subject Type Homework Help
subject Pages 9
subject Words 2859
subject Authors Joey F. George, Joseph S. Valacich

Unlock document.

This document is partially blurred.
Unlock all pages and 1 million more documents.
Get Access
page-pf1
Essentials of Systems Analysis and Design, 6e (Valacich)
Chapter 7 Structuring System Requirements: Conceptual Data Modeling
1) The characteristics of data captured during data modeling are crucial in the design of
databases, programs, computer screens, and printed reports.
Classification: Concept
2) Processes, rather than data, are the most complex aspects of many modern information
systems.
Classification: Concept
3) The purpose of the conceptual data model is to show as many rules about the meaning and
interrelationships among data as possible.
Classification: Concept
4) The names of data stores on primitive-level data flow diagrams often correspond to the names
of data entities in entity-relationship (E-R) diagrams.
Classification: Concept
5) The primary deliverable for the conceptual data-modeling step within the analysis phase is an
entity-relationship diagram.
Classification: Concept
1
page-pf2
6) A deliverable from conceptual data modeling is a set of entries about data objects to be stored
in the project dictionary or repository.
Classification: Concept
7) The top-down approach to data modeling derives a data model by reviewing specific business
documents.
Classification: Concept
8) An analyst would ask, "What must we know about each object in order to run a business?" in
order to determine relationships, their cardinality, and degrees.
Classification: Application
9) In order to determine security controls and understand who really knows the meaning of data,
an analyst might ask, "What natural activities or transactions of the business involve handling
data about several objects of the same or different type?"
Classification: Application
10) In order to determine the integrity rules, minimum and maximum cardinality, and time
dimensions of data, an analyst might ask, "Are values for data characteristics limited in any
way?"
Classification: Application
2
page-pf3
11) An entity is a person, place, object, event, or concept in the user environment about which
the organization wishes to maintain data.
Classification: Concept
12) Book, supplier, and state are examples of entity types.
Classification: Application
13) Since a name represents a set of entities, it is plural on an entity-relationship diagram.
Classification: Concept
14) Use a verb or verb phrase to name an entity.
Classification: Concept
15) Social security number, last name, and first name are examples of entity types.
Classification: Application
16) A true data entity will have many possible instances, each with a distinguishing
characteristic, as well as one or more other descriptive pieces of data.
Classification: Concept
3
page-pf4
17) An entity instance is a single occurrence of an entity type.
Classification: Concept
18) Employee identification number, name, address, and skill are examples of attributes.
Classification: Application
19) An order number is a good example of a candidate key.
Classification: Application
20) A faculty identification number could be used as an identifier.
Classification: Application
21) A primary key should be null.
Classification: Concept
22) An identifier is a candidate key that has been selected as the unique, identifying characteristic
for an entity type.
Classification: Concept
4
page-pf5
23) When selecting an identifier, one should choose a candidate key that will not change its value
over the life of each instance of the entity type.
Classification: Concept
24) Analysts should use intelligent keys as identifiers.
Classification: Concept
25) Analysts should consider substituting single-attribute surrogate keys for large composite
keys.
Classification: Concept
26) When referencing an employee entity, an employee's skills are an example of a multivalued
attribute.
Classification: Application
27) One way to handle repeating data within an entity is to separate the repeating data into
another entity, called a weak entity.
Classification: Concept
28) A multivalued attribute is an attribute that may take on more than one value for each entity
instance.
Classification: Concept
5
page-pf6
29) A repeating group is a set of two or more multivalued attributes that are logically related.
Classification: Concept
30) A join is an association between the instances of one or more entity types that is of interest to
the organization.
Classification: Concept
31) Relationships are labeled with verb phrases.
Classification: Concept
32) The goal of conceptual data modeling is to capture as much of the meaning of data as
possible.
Classification: Concept
33) A ternary relationship is a relationship between instances of one entity type.
Classification: Concept
34) A unary relationship is the most common type of relationship encountered in data modeling.
Classification: Concept
6
page-pf7
35) A ternary relationship is the equivalent of three binary relationships.
Classification: Concept
36) Cardinality is the number of instances of entity B that can (or must) be associated with each
instance of entity A.
Classification: Concept
37) The minimum cardinality of a relationship is the minimum number of instances of entity B
that may be associated with each instance of entity A.
Classification: Concept
38) A plural relationship is a relationship that the data modeler chooses to model as entity type.
Classification: Concept
39) A relationship must be turned into an associative entity when the associative entity has other
relationships with entities besides the relationship that caused its creation.
Classification: Concept
40) Ideally, each data store on a primitive data-flow diagram will be an individual attribute.
Classification: Concept
7
page-pf8
41) Conceptual data modeling for an Internet-based electronic commerce application differs
significantly from the process followed when analyzing the data needs for other types of
applications.
Classification: Concept
42) During the designing the human interface step of the design phase, you would enumerate
different potential implementation environments that could be used to deliver the different sets of
capabilities.
Classification: Concept
43) In theory, if there are four sets of requirements, three implementation environments, and four
sources of application software, then there would be thirty-six possible design strategies.
Classification: Application
44) In theory, if there are six sets of requirements, four implementation environments, and five
sources of application software, then there would be one hundred twenty possible design
strategies.
Classification: Application
45) A good number of alternatives to generate is five.
Classification: Concept
8
page-pf9
46) Cost is the primary focus of high-end alternatives.
Classification: Concept
47) The minimum requirements for a new system are also its mandatory features.
Classification: Concept
48) Essential features are those that everyone agrees are necessary to solve the problem or meet
the opportunity.
Classification: Concept
49) Conceptual data modeling is typically done in parallel with other requirements analysis and
structuring steps during:
A) systems planning and selection.
B) systems design.
C) systems analysis.
D) systems implementation and operation.
E) systems evaluation.
Classification: Concept
50) The most common format used for data modeling is:
A) state-transition diagramming.
B) entity-relationship diagramming.
C) process modeling.
D) logic modeling.
E) a flowchart.
Classification: Concept
9
page-pfa
51) During systems analysis:
A) a conceptual data model (E-R with attributes) is prepared.
B) a logical model (relational) is prepared.
C) physical files and database designs are prepared.
D) an enterprise-wide data model is prepared.
E) database and file definitions are prepared.
Classification: Concept
52) The primary deliverable from the conceptual data-modeling step within the analysis phase is:
A) a state-transition diagram.
B) an entity-relationship diagram.
C) a context data flow diagram.
D) a decision table.
E) Structured English.
Classification: Concept
53) Which of the following is a true statement?
A) A data model explains what the organization does and what rules govern how work is done in
the organization.
B) To construct a data model, you need to know how data are processed.
C) To construct a data model, you need to know when data are processed.
D) A data flow diagram graphically illustrates the structure and relationships among data items.
E) During conceptual data modeling, the preparation of a Network diagram is necessary.
Classification: Concept
10

Trusted by Thousands of
Students

Here are what students say about us.

Copyright ©2022 All rights reserved. | CoursePaper is not sponsored or endorsed by any college or university.