Deck 8: Data Modeling and Analysis

Question 1

Data modeling is a technique for defining business requirements for a database.

Answer 1

True

Question 2

Data modeling is a technique for organizing and documenting a system's logical and physical models.

Answer 2

False

Question 3

Data modeling is sometimes called database modeling because a data model is eventually implemented as a database.

Answer 3

True

Question 4

An entity is something about which the business needs to store data.

Question 5

An entity is a class of persons, places, objects, events or concepts about which we need to capture and store data.

Question 6

An identity is a class of persons, places, objects, events, or concepts about which we need to capture and store data.

Question 7

An entity existence is a single occurrence of an entity.

Question 8

An attribute is a descriptive property or characteristic of an entity.

Question 9

A compound attribute is one that actually consists of other attributes that are logically grouped together.

Question 10

A compound attribute is an attribute that will be expanded into a separate entity.

Question 11

The data type of an attribute defines what type of data can be stored in that attribute.

Question 12

Example data types include: numbers, text, memo, date, time, yes/no, Boolean, value set, or image.

Question 13

The domain of an attribute defines what values an attribute can legitimately take on.

Question 14

The domain value for an attribute is the value that will be recorded if not specified by the user.

Question 15

A key is an attribute, or group of attributes, that assumes a unique value for each entity instance. It is sometimes called an identifier.

Question 16

A key is an attribute or group of attributes that assumes a unique value for each entity instance. It is sometimes called the domain of the attribute.

Question 17

A concatenated key is a group of attributes that uniquely identifies an instance of an entity.

Question 18

A concatenated key is also known as a composite key or a compound key.

Question 19

A candidate key must be a single attribute.

Question 20

A candidate key may be a single attribute or a concatenated key.

Question 21

A primary key is that candidate key that will most commonly be used to uniquely identify a single entity instance.

Question 22

An example of domain would be an attribute called grade where the values could only be A, B, C, D, E, or F.

Question 23

An alternate key is also known as a secondary key.

Question 24

A subsetting criteria is an attribute or concatenated attribute whose finite values divide all entity instances into useful subsets.

Question 25

A subsetting criteria is also known as an inversion entry.

Question 26

A subsetting criteria is a domain of attributes whose values are limitless to allow for a variety of subsets to be constructed from a database.

Question 27

A relationship is a natural business association that exists between one or more entities.

Question 28

A relationship may represent an event that links the entities or merely a physical affinity that exists between the entities.

Question 29

All data model relationships are unidirectional.

Question 30

Because all relationships are bi-directional in an entity relationship diagram, cardinality must be defined in both directions for every relationship.

Question 31

Conceptually cardinality defines the minimum and maximum attributes that can be added to an entity.

Question 32

The domain of a relationship is the number of entities that participate in the relationship.

Question 33

A recursive relationship is when only one entity participates in the relationship.

Question 34

A recursive relationship is a relationship with a degree of infinity, because there is no limit to how many entities participate in the relationship.

Question 35

A recursive relationship identifies a relationship that may exist between different instances of the same entity.

Question 36

A ternary relationship is a relationship among three entities.

Question 37

The relationship between a student entity and a curriculum entity would be classified as recursive.

Question 38

In a one-to-many relationship, the parent is the entity on the "one" side.

Question 39

A foreign key in a child entity always matches the primary key in the parent entity.

Question 40

A foreign key in the parent entity always matches the primary key in the child entity.

Question 41

Nonidentifying relationships are those in which each of the participating entities has its own independent primary key. That is, none of the primary key attributes is shared.

Question 42

Nonidentifying relationships are those in which each of the participating entities has dependent primary keys.

Question 43

Identifying relationships are those in which the parent entity contributes its primary key to become part of the primary key of the child entity.

Question 44

A nonspecific relationship is a many-to-many relationship.

Question 45

A non-specific relationship is one in which many instances of one entity are associated with many instances of another entity.

Question 46

A many-to-many relationship is one in which many entities are associated with other attributes of a different entity.

Question 47

Generalization is a technique wherein the attributes that are common to several types of an entity are grouped into their own entity, called a supertype.

Question 48

Generalization is a technique wherein the domains common to several types of attributes are grouped into their own entity, called an associate entity.

Question 49

An entity subtype is an entity whose instances inherit some common attributes from an entity supertype and then add other attributes that are unique to an instance of the subtype.

Question 50

An entity supertype is an entity whose instances inherit some common attributes from an entity subtype and then add other attributes that are unique to an instance of the supertype.

Question 51

An enterprise data model typically identifies only the most fundamental of entities of the enterprise.

Question 52

An enterprise data model typically identifies and defines only the most complex entities used by the enterprise.

Question 53

The data model for a single information system is usually called an application data model.

Question 54

The context data model is prepared during the problem analysis phase and only includes entities and relationships, but no attributes.

Question 55

The requirements analysis results in a logical data model that is developed in stages as follows: (1) context data model; (2) key-based data model; (3) fully attributed data model; and (4) the normalized data model.

Question 56

The requirements analysis results in a physical data model that is developed in stages as follows: (1) normalized data model; (2) key-based data model; (3) fully attributed data model; and (4) the context data model.

Question 57

During systems design, the logical data model will be transformed into a physical data model.

Question 58

During the requirements phase, the physical data model is transformed into the logical data model.

Question 59

Another name for the logical data model is the database schema.

Question 60

The data model is metadata - that is, it is data about data.

Question 61

The value of a key should not change over the lifetime of each entity instance.

Question 62

The value of a key can change over the lifetime of each entity instance.

Question 63

The value of a key can be null.

Question 64

Controls must be installed to ensure that the value of a key is valid.

Question 65

An intelligent key is a business code whose structure communicates data about an entity instance (such as its classification, size or other properties).

Question 66

The authors of your textbook recommend the use of intelligent keys since they can be quickly processed by humans without the assistance of a computer.

Question 67

Some experts suggest that you avoid the use of intelligent keys when designing your data model. They argue that because characteristics can change it violates the rule that the value of a key should not change over the lifetime of each entity instance.

Question 68

Serial codes assign sequentially generated numbers to entity instances.

Question 69

Alphabetic codes use finite combinations of letters (and possibly numbers) to describe entity instances.

Question 70

In significant position codes, each digit or group of digits describes a measurable or identifiable characteristic of the entity instance.

Question 71

Significant position codes are frequently used to code inventory items.

Question 72

Hierarchical codes provide a top-down interpretation for an entity instance by factoring an item into its group, subgroup and so forth.

Question 73

If use-case narratives have been written during the requirements analysis phase, analysts can scan them for verbs to discover data attributes and entities.

Question 74

Once the data model has been defined, it is trivial to identify the remaining data attributes.

Question 75

Many organizations have naming standards and approved abbreviations for data attributes.

Question 76

A good data model is simple.

Question 77

A good data model is essentially nonredundant.

Question 78

In a good data mode, each data attribute describes at most one entity.

Question 79

A good data model should be flexible and adaptable to future needs.

Question 80

A good data model is inflexible because it is an accurate representation of the business data requirements.