Deck 7: Structuring System Requirements: Conceptual Data Modeling
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Deck 7: Structuring System Requirements: Conceptual Data Modeling
1
A faculty identification number could be used as an identifier.
True
2
The primary deliverable for the conceptual data-modeling step within the analysis phase is an entity-relationship diagram.
True
3
An entity is a person, place, object, event, or concept in the user environment about which the organization wishes to maintain data.
True
4
Since a name represents a set of entities, it is plural on an entity-relationship diagram.
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5
Social security number, last name, and first name are examples of entity types.
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6
An entity instance is a single occurrence of an entity type.
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7
Use a verb or verb phrase to name an entity.
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8
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.
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9
The top-down approach to data modeling derives a data model by reviewing specific business documents.
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10
Book, supplier, and state are examples of entity types.
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11
A deliverable from conceptual data modeling is a set of entries about data objects to be stored in the project dictionary or repository.
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12
The characteristics of data captured during data modeling are crucial in the design of databases, programs, computer screens, and printed reports.
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13
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?"
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14
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?"
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15
Employee identification number, name, address, and skill are examples of attributes.
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16
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.
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17
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.
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18
Processes, rather than data, are the most complex aspects of many modern information systems.
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19
The purpose of the conceptual data model is to show as many rules about the meaning and interrelationships among data as possible.
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20
An order number is a good example of a candidate key.
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21
A plural relationship is a relationship that the data modeler chooses to model as entity type.
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22
Relationships are labeled with verb phrases.
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23
A repeating group is a set of two or more multivalued attributes that are logically related.
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24
One way to handle repeating data within an entity is to separate the repeating data into another entity, called a weak entity.
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25
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.
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26
Cardinality is the number of instances of entity B that can (or must) be associated with each instance of entity A.
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27
A primary key should be null.
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28
A ternary relationship is the equivalent of three binary relationships.
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29
A ternary relationship is a relationship between instances of one entity type.
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30
A join is an association between the instances of one or more entity types that is of interest to the organization.
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31
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.
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32
An identifier is a candidate key that has been selected as the unique, identifying characteristic for an entity type.
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33
A unary relationship is the most common type of relationship encountered in data modeling.
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34
Analysts should use intelligent keys as identifiers.
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35
The goal of conceptual data modeling is to capture as much of the meaning of data as possible.
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36
Analysts should consider substituting single-attribute surrogate keys for large composite keys.
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37
A multivalued attribute is an attribute that may take on more than one value for each entity instance.
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38
When referencing an employee entity, an employee's skills are an example of a multivalued attribute.
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39
Ideally, each data store on a primitive data-flow diagram will be an individual attribute.
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40
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.
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41
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.
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42
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.
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43
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.
A) systems planning and selection.
B) systems design.
C) systems analysis.
D) systems implementation and operation.
E) systems evaluation.
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44
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.
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.
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45
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.
A) a state-transition diagram.
B) an entity-relationship diagram.
C) a context data flow diagram.
D) a decision table.
E) Structured English.
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46
Cost is the primary focus of high-end alternatives.
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47
The minimum requirements for a new system are also its mandatory features.
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48
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.
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49
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.
A) state-transition diagramming.
B) entity-relationship diagramming.
C) process modeling.
D) logic modeling.
E) a flowchart.
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50
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.
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.
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51
Asking system users and business managers, "What are the subjects of the business?" would help determine:
A) the data entities and their descriptions.
B) the candidate key.
C) attributes and secondary keys.
D) relationships and their cardinality and degrees.
E) integrity rules, minimum and maximum cardinality, and time dimensions of data.
A) the data entities and their descriptions.
B) the candidate key.
C) attributes and secondary keys.
D) relationships and their cardinality and degrees.
E) integrity rules, minimum and maximum cardinality, and time dimensions of data.
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52
Essential features are those that everyone agrees are necessary to solve the problem or meet the opportunity.
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53
The data modeling perspective that derives the business rules for a data model from an intimate understanding of the nature of the business, rather than from any specific information requirements in screens, reports, or business forms, is referred to as the:
A) top-down approach.
B) bottom-up approach.
C) overview approach.
D) business approach.
E) conceptual approach.
A) top-down approach.
B) bottom-up approach.
C) overview approach.
D) business approach.
E) conceptual approach.
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54
A person, place, object, event, or concept in the user environment about which the organization wishes to maintain data refers to a(n):
A) attribute.
B) data element.
C) relationship.
D) entity.
E) process.
A) attribute.
B) data element.
C) relationship.
D) entity.
E) process.
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55
Asking system users and managers, "Who is responsible for establishing legitimate values for these data?" helps determine:
A) the candidate key.
B) security controls and understanding who really knows the meaning of data.
C) relationships and their cardinality and degrees.
D) attributes and secondary keys.
E) integrity rules, minimum and maximum cardinality, and time dimensions of data.
A) the candidate key.
B) security controls and understanding who really knows the meaning of data.
C) relationships and their cardinality and degrees.
D) attributes and secondary keys.
E) integrity rules, minimum and maximum cardinality, and time dimensions of data.
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56
On an entity-relationship diagram, a rectangle represents a(n):
A) data flow.
B) entity.
C) multivalued attribute.
D) repeating group.
E) relationship.
A) data flow.
B) entity.
C) multivalued attribute.
D) repeating group.
E) relationship.
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57
Gathering the information you need for data modeling by reviewing specific business documents handled within the system describes the:
A) bottom-up approach.
B) conceptual approach.
C) top-down approach.
D) investigative approach.
E) business approach.
A) bottom-up approach.
B) conceptual approach.
C) top-down approach.
D) investigative approach.
E) business approach.
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58
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.
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59
Reviewing computer screens, reports, and business forms for the purpose of gaining an understanding of data is indicative of the:
A) investigative approach.
B) business approach.
C) bottom-up approach.
D) top-down approach.
E) conceptual approach.
A) investigative approach.
B) business approach.
C) bottom-up approach.
D) top-down approach.
E) conceptual approach.
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60
A good number of alternatives to generate is five.
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61
A renewal is an example of a(n):
A) data element.
B) attribute.
C) entity.
D) relationship.
E) action stub.
A) data element.
B) attribute.
C) entity.
D) relationship.
E) action stub.
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62
An association between the instances of one or more entity types that is of interest to the organization best defines:
A) occurrence.
B) relationship.
C) natural connection.
D) cardinality.
E) entity link.
A) occurrence.
B) relationship.
C) natural connection.
D) cardinality.
E) entity link.
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63
A relationship between the instances of one entity type is a:
A) unary relationship.
B) binary relationship.
C) ternary relationship.
D) singular occurrence.
E) partnership occurrence.
A) unary relationship.
B) binary relationship.
C) ternary relationship.
D) singular occurrence.
E) partnership occurrence.
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64
An attribute that can have more than one value for each entity instance is referred to as:
A) a gerund.
B) a multivalued attribute.
C) a nonexclusive attribute.
D) a data replica.
E) composite attribute
A) a gerund.
B) a multivalued attribute.
C) a nonexclusive attribute.
D) a data replica.
E) composite attribute
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65
A set of two or more multivalued attributes that are logically related defines:
A) relationship.
B) associative entity.
C) repeating group.
D) class.
E) repeating entity.
A) relationship.
B) associative entity.
C) repeating group.
D) class.
E) repeating entity.
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66
A candidate key that has been selected as the unique, identifying characteristic for an entity type is called a(n):
A) attribute.
B) identifier.
C) secondary key.
D) gerund.
E) index.
A) attribute.
B) identifier.
C) secondary key.
D) gerund.
E) index.
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67
The number of entity types that participate in a relationship refers to:
A) cardinality.
B) association.
C) count.
D) degree.
E) normalization.
A) cardinality.
B) association.
C) count.
D) degree.
E) normalization.
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68
A named property or characteristic of an entity that is of interest to the organization defines:
A) attribute.
B) relationship.
C) instance.
D) associative entity.
E) data flow.
A) attribute.
B) relationship.
C) instance.
D) associative entity.
E) data flow.
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69
Vehicle identification number, color, weight, and horsepower best exemplify:
A) entities.
B) entity types.
C) data markers.
D) identifiers.
E) attributes.
A) entities.
B) entity types.
C) data markers.
D) identifiers.
E) attributes.
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70
On an entity-relationship diagram, the entity's identifier is:
A) identified by using a double-lined ellipse.
B) underlined on an E-R diagram.
C) bold on an E-R diagram.
D) written in all capital letters on an E-R diagram.
E) placed in italics.
A) identified by using a double-lined ellipse.
B) underlined on an E-R diagram.
C) bold on an E-R diagram.
D) written in all capital letters on an E-R diagram.
E) placed in italics.
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71
If STUDENT and COURSE participate in a relationship, this is an example of a(n):
A) unary relationship.
B) coupled relationship.
C) binary relationship.
D) ternary relationship.
E) extraordinary relationship.
A) unary relationship.
B) coupled relationship.
C) binary relationship.
D) ternary relationship.
E) extraordinary relationship.
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72
If each employee can have more than one skill, then skill is referred to as a:
A) gerund.
B) multivalued attribute.
C) nonexclusive attribute.
D) repeating attribute.
E) data replica.
A) gerund.
B) multivalued attribute.
C) nonexclusive attribute.
D) repeating attribute.
E) data replica.
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73
A product is an example of a(n):
A) data element.
B) attribute.
C) entity.
D) relationship.
E) process.
A) data element.
B) attribute.
C) entity.
D) relationship.
E) process.
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74
The number of instances of entity B that can (or must) be associated with each instance of entity A refers to:
A) cardinality.
B) domain.
C) ternary occurrence.
D) participation level.
E) join level.
A) cardinality.
B) domain.
C) ternary occurrence.
D) participation level.
E) join level.
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75
A relationship between instances of two entity types is a:
A) unary relationship.
B) binary relationship.
C) ternary relationship.
D) multiple occurrence.
E) partnership occurrence.
A) unary relationship.
B) binary relationship.
C) ternary relationship.
D) multiple occurrence.
E) partnership occurrence.
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76
A collection of entities that share common properties or characteristics best defines:
A) entity type.
B) entity instance.
C) entity occurrence.
D) entity collection.
E) data set.
A) entity type.
B) entity instance.
C) entity occurrence.
D) entity collection.
E) data set.
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77
A single occurrence of an entity type defines:
A) entity instance.
B) entity appearance.
C) attribute.
D) data element.
E) multivalued attribute.
A) entity instance.
B) entity appearance.
C) attribute.
D) data element.
E) multivalued attribute.
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78
An attribute (or combination of attributes) that uniquely identifies each instance of an entity type defines:
A) data element occurrence.
B) trigger.
C) candidate key.
D) associative entity.
E) data marker.
A) data element occurrence.
B) trigger.
C) candidate key.
D) associative entity.
E) data marker.
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79
When selecting an identifier, one should:
A) use intelligent keys.
B) use large composite keys instead of single-attribute surrogate keys.
C) choose a candidate key that will not change its value over the life of each instance of the entity type.
D) choose a candidate key such that for each instance of the entity, the attribute is guaranteed to have valid values or is null.
E) choose a candidate key that allows for duplicate values.
A) use intelligent keys.
B) use large composite keys instead of single-attribute surrogate keys.
C) choose a candidate key that will not change its value over the life of each instance of the entity type.
D) choose a candidate key such that for each instance of the entity, the attribute is guaranteed to have valid values or is null.
E) choose a candidate key that allows for duplicate values.
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80
A ternary relationship occurs when a simultaneous relationship exists among instances of:
A) the same entity.
B) two entity types.
C) three entity types.
D) four entity types.
E) nine entity types.
A) the same entity.
B) two entity types.
C) three entity types.
D) four entity types.
E) nine entity types.
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