Chapter 7 Structuring System Requirements: Conceptual Data Modeling

An entity instance...

...is a single occurrence of an entity type.

Item description is? a. Attribute b. Entity c. Relationship

A

inventory item is? a. Attribute b. Entity c. Relationship

B

A relationship that the data modeler chooses to model as an entity type best defines: a. recursive relationship. b. associative entity. c. domain. d. complex relationship. e. complex entity.

b. associative entity

Quantity sold is? a. Attribute b. Entity c. Relationship

A

sells is? a. Attribute b. Entity c. Relationship

C

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.

T

Invoice is? a. Attribute b. Entity c. Relationship

B

Product is? a. Attribute b. Entity c. Relationship

B

Sale is? a. Attribute b. Entity c. Relationship

B

invoice item is? a. Attribute b. Entity c. Relationship

B

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.

is order on is?a. Attribute b. Entity c. Relationship

C

received on is? a. Attribute b. Entity c. Relationship

C

. Ideally, each data store on a primitive data-flow diagram will be an individual entity.

T

. One way to handle repeating data within an entity is to separate the repeating data into another entity, called a weak entity

T

. The top-down approach to data modeling derives a data model from an intimate understanding of the nature of the business.

T

4. 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.

T

A multivalued attribute is an attribute that may take on more than one value for each entity instance.

T

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.

T

An entity is a person, place, object, event, or concept in the user environment about which the organization wishes to maintain data.

T

An identifier is a candidate key that has been selected as the unique, identifying characteristic for an entity type

T

Analysts should consider substituting single-attribute surrogate keys for large composite keys

T

Cardinality is the number of instances of entity B that can (or must) be associated with each instance of entity A.

T

Referencing an employee entity, an employee's skills are an example of a multivalued attribute.

T

Relationships are labeled with verb phrases.

T

The characteristics of data captured during data modeling are crucial in the design of databases, programs, computer screens, and printed reports.

T

The goal of conceptual data modeling is to capture as much of the meaning of data as possible.

T

The primary deliverable for the conceptual data-modeling step within the analysis phase is an entity-relationship diagram

T

The purpose of the conceptual data model is to show as many rules about the meaning and interrelationships among data as possible.

T

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.

T

. Process, logic, and data-model descriptions of a system must be consistent and complete since: a. they each describe different but complementary views of the same information system. b. they are prepared during the analysis phase. c. they are constructed in parallel by separate analyst teams. d. a data model indicates when the data are processed. e. a data model shows how the data are processed

a. they each describe different but complementary views of the same information system

. Vehicle identification number, color, weight, and horsepower best exemplify: a. entities. b. entity types. c. data markers. d. identifiers. e. attributes

e. attributes

A detailed, logical, and graphical representation of the entities, associations, and data elements for an organization or business area best describes a(n): a. logic model. b. data-flow diagram. c. structure chart. d. entity-relationship diagram or E-R diagram. e. data tree

d. entity-relationship diagram or E-R diagram.

. 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.

d. entity.

An entity-relationship diagram (E-R diagram)...

... is a detailed, logical, and graphical representation of the entities, associations, and data elements for an organization or business area.

An attribute ...

... is a named property or characteristic of an entity that is of interest to the organization.

Cardinality....

.... refers to the number of instances of entity B that can (or must) be associated with each instance of entity A.

A top-down approach...

...derives the data model from an intimate understanding of the nature of the business, rather than from any specific information requirements in computer displays, reports, or business forms.

An identifier...

...is a candidate key that has been selected as the unique, identifying characteristic for an entity type

An entity type...

...is a collection of entities that share common properties or characteristics

An entity...

...is a person, place, object, event, or concept in the user environment about which the organization wishes to maintain data.

A relationship...

...is an association between the instances of one or more entity types that is of interest to the organization.

A candidate key...

...is an attribute (or combination of attributes) that uniquely identifies each instance of an entity type.

An associative entity...

...is an entity type that associates the instances of one or more entity types and contains attributes that are peculiar to the relationship between those entity instances.

A bottom-up approach...

..reviews specific business documents, such as computer displays, reports, and business forms, handled within the system.

A logical data model is prepared during systems analysis.

F

A primary key should be null.

F

An enterprise-wide data model is prepared during systems implementation and operation

F

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

F

During systems design, a conceptual data model with attributes is prepared.

F

Processes, rather than data, are the most complex aspects of many modern information systems.

F

Use a verb or verb phrase to name an entity.

F

When constructing a data model, the analyst needs to know how, when, and where data are processed.

F

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.

. 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.

. A single occurrence of an entity type defines: a. entity instance. b. entity appearance. c. attribute. d. data element. e. entity type

a. entity instance.

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.

. Asking system users and business managers "How many instances of each object might exist?" 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.

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.

b. an entity-relationship diagram.

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

b. entity-relationship diagramming

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.

b. identifier

. Which of the following is a true statement? a. Data entities correspond to sources/sinks on a data flow diagram. b. Relationships correspond to data flows on a data flow diagram. c. A data entity will have many possible instances. d. Verbs are used to name entity types. e. An entity type is described many times in the data model.

c. A data entity will have many possible instances.

Which of the following is a true statement? a. Data characteristics are dynamic. b. A data model explains the transient form of an organization. c. An information system design based on a data orientation, rather than a process or logic orientation, should have a longer useful life. d. Data flow paths are permanent. e. A data model graphically represents the processes that capture, manipulate, store, and distribute data between a system and its environment and among components within a system

c. An information system design based on a data orientation, rather than a process or logic orientation, should have a longer useful life.

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

c. bottom-up approach

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.

c. candidate key.

A product is an example of a(n): a. data element. b. attribute. c. entity. d. relationship. e. process.

c. entity.

A renewal is an example of a(n): a. data element. b. attribute. c. entity. d. relationship. e. action stub.

c. entity.

. 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.

c. systems analysis.

. If entity B is a mandatory participant, then: a. the minimum cardinality of the relationship is two. b. the minimum cardinality of the relationship cannot be defined. c. the minimum cardinality of the relationship is one. d. the minimum cardinality of the relationship is optional. e. the join level is not null.

c. the minimum cardinality of the relationship is one.