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D427 - Data Management - Applications > 4. Database Design > Flashcards

4. Database Design Flashcards

1
Q

entity-relationship model

A

An entity-relationship model is a high-level representation of data requirements, ignoring implementation details.

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2
Q

entity

A

A person, place, product, concept, or activity.

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3
Q

relationship

A

a statement about two entities.

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4
Q

attribute

A

descriptive property of an entity.

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5
Q

reflexive relationship

A

A reflexive relationship relates an entity to itself.

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6
Q

entity-relationship diagram / ER diagram

A

An entity-relationship diagram, commonly called an ER diagram, is a schematic picture of entities, relationships, and attributes.

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7
Q

glossary / data dictionary / repository

A

A glossary, also known as a data dictionary or repository, documents additional detail in text format.

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8
Q

entity type

A

An entity type is a set of things. Ex: All employees in a company.

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9
Q

relationship type

A

A relationship type is a set of related things. Ex: Employee-Manages-Department is a set of (employee, department) pairs, where the employee manages the department.

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10
Q

attribute type

A

An attribute type is a set of values. Ex: All employee salaries.

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11
Q

entity instance

A

An entity instance is an individual thing. Ex: The employee Sam Snead.

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12
Q

relationship instance

A

A relationship instance is a statement about entity instances. Ex: ‘Maria Rodriguez manages Sales.’

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13
Q

attribute instance

A

An attribute instance is an individual value. Ex: The salary $35,000.

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14
Q

Analysis

A

Analysis develops an entity-relationship model, capturing data requirements while ignoring implementation details.

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15
Q

Logical design

A

Logical design converts the entity-relationship model into tables, columns, and keys for a particular database system.

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16
Q

Physical design

A

Physical design adds indexes and specifies how tables are organized on storage media.

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17
Q

cardinality

A

In entity-relationship modeling, cardinality refers to maxima and minima of relationships and attributes.

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18
Q

Relationship maximum

A

Relationship maximum is the greatest number of instances of one entity that can relate to a single instance of another entity.

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19
Q

singular / plural

A

A related entity is singular when the maximum is one and plural when the maximum is many.

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20
Q

Relationship minimum

A

Relationship minimum is the least number of instances of one entity that can relate to a single instance of another entity.

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21
Q

optional / required

A

A related entity is optional when the minimum is zero and required when the minimum is one.

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22
Q

Attribute maximum

A

Attribute maximum is the greatest number of attribute values that can describe each entity instance. Attribute maximum is usually specified as one (singular) or many (plural).

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23
Q

Attribute minimum

A

Attribute minimum is the least number of attribute values that can describe each entity instance. Attribute minimum is usually specified as zero (optional) or one (required).

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24
Q

unique attribute

A

Each value of a unique attribute describes at most one entity instance.

25
Q

identifying attribute

A

An identifying attribute is unique, singular, and required.

26
Q

identify

A

Identifying attribute values correspond one-to-one to, or identify, entity instances.

27
Q

strong entity

A

A strong entity has one or more identifying attributes.

28
Q

weak entity / identifying relationship / identifying entity

A

A weak entity does not have an identifying attribute. Instead, a weak entity usually has a relationship, called an identifying relationship, to another entity, called an identifying entity. Cardinality of the identifying entity is 1(1).

29
Q

subtype entity / supertype entity

A

A subtype entity is a subset of another entity type, called the supertype entity.

30
Q

IsA relationship

A

A supertype entity identifies its subtype entities. The identifying relationship is called an IsA relationship.

31
Q

Similar entities

A

Similar entities are entities that have many common attributes and relationships.

32
Q

partition

A

A partition of a supertype entity is a group of mutually exclusive subtype entities.

33
Q

partition attribute

A

Each partition corresponds to an optional partition attribute of the supertype entity.

34
Q

crow’s foot notation

A

Variations in cardinality conventions are common. One popular convention, called crow’s foot notation, depicts cardinality as a circle (zero), a short line (one), or three short lines (many). The three short lines look like a bird’s foot, hence the name ‘crow’s foot notation’.

35
Q

subject area

A

Decompose a complex model into a group of related entities, called a subject area.

36
Q

independent / dependent

A

Refer to strong entities as independent and weak entities as dependent.

37
Q

Unified Modeling Language / UML

A

Unified Modeling Language, or UML, is commonly used for software development. Software data structures are similar to database structures, so UML includes ER conventions.

38
Q

IDEF1X

A

IDEF1X stands for Information DEFinition version 1X. IDEF1X became popular, in part, due to early adoption by the United States Department of Defense.

39
Q

Chen notation

A

Chen notation appeared in an early ER modeling paper by Peter Chen. Chen notation is not standardized but often appears in literature and tools.

40
Q

strong table

A

A strong entity becomes a strong table. The primary key must be unique and non-NULL, and should be stable, simple, and meaningless. Single-column primary keys are best, but if no such column exists, a composite primary key may have the required properties.

41
Q

artificial key

A

An artificial key is a single-column primary key created by the database designer when no suitable single-column or composite primary key exists.

42
Q

subtype table

A

A subtype entity becomes a subtype table.

43
Q

weak table

A

A weak entity becomes a weak table.

44
Q

depends on

A

Column A depends on column B means each B value is related to at most one A value.

45
Q

functional dependence

A

Dependence of one column on another is called functional dependence.

46
Q

Multivalued dependence / join dependence

A

Multivalued dependence and join dependence entail dependencies between three or more columns.

47
Q

Redundancy

A

Redundancy is the repetition of related values in a table.

48
Q

Normal forms

A

Normal forms are rules for designing tables with less redundancy.

49
Q

first normal form

A

Every cell of a table contains exactly one value. A table is in first normal form when, in addition, the table has a primary key.

50
Q

second normal form

A

A table is in second normal form when all non-key columns depend on the whole primary key.

51
Q

third normal form

A

Informally, a table is in third normal form when all non-key columns depend on the key, the whole key, and nothing but the key. A formal definition appears elsewhere in this material.

52
Q

candidate key / Minimal

A

A candidate key is a simple or composite column that is unique and minimal. Minimal means all columns are necessary for uniqueness.

53
Q

non-key

A

A non-key column is a column that is not contained in a candidate key.

54
Q

third normal form

A

A table is in third normal form if, whenever a non-key column A depends on column B, then B is unique. Columns A and B may be simple or composite.

55
Q

Boyce-Codd normal form

A

A table is in Boyce-Codd normal form if, whenever column A depends on column B, then B is unique. Columns A and B may be simple or composite.

56
Q

Normalization

A

Normalization eliminates redundancy by decomposing a table into two or more tables in higher normal form.

57
Q

depends on

A

Column A depends on column B when each B value is related to at most one A value. A and B may be simple or composite columns.

58
Q

Boyce-Codd normal form

A

In a Boyce-Codd normal form table, if column A depends on column B, then B must be unique.

59
Q

Denormalization

A

Denormalization means intentionally introducing redundancy by merging tables.

D427 - Data Management - Applications (15 decks)

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