Overlapping subtypes are subtypes that contain _____ subsets of the supertype entity set.

  1. In modeling terms, an (        ) is a generic type that is related to one or more entity subtypes

    Entity Supertype

  2. The (       ) contains common characteristics, and the entity subtypes contain the unique characteristics of each entity subtype

    Entity Supertype

  3. Each supertypes and subtypes are organized in a ( ), which depicts the arrangement of the higher-level entity supertypes (parent entities) and lower-level entity subtypes

    Specialization Hierachy

  4. A specialization hierarchy provides the means to:

    • - Support attribute inheritance
    • - Define a special supertype attribute known as the subtype discriminator
    • - Define disjoint/overlapping constraints and complete/partial constraints

  5. A ( ) is the attribute in the supertype entity that determines to which subtype the supertype occurence is related

    Subtype Discriminator

  6. ( ) are subtypes that contain nonunique subsets of the supertype entity set; that is each entity instance of the supertype may appear in more than one subtype

    Overlapping subtypes

  7. The ( ) specifies whether each entity supertype occurrence must also be a member of at least one subtype.  The ( ) can be partial or total

    Completeness Constraint

  8. (Symbolized by a circle over a single line) means that not every supertype occurrence is a member of a subtype

    Partial Completeness

  9. ( ) (Symbolized by a circle over a double line) means that every supertype occurrence must be a member of at least one subtype

    Total Completeness

  10. ( ) is the top-down process of identifying lower-level, more specific entity subtypes from a higher-level entity supertype.  ( ) is based on grouping unique characteristics and relationships of the subtypes

    Specialization

  11. ( ) is the bottom-up process of identifying a higher-level, more generic entity supertype from lower-level entity

    Generalization

  12. An ( ) is a "virtual" entity type used to represent multiple entities and relationships in the ERD.  An () is formed by combining multiple interrelated entities into a single abstract entity object.

    Entity Cluster

  13. A ( ) or ( ) is a real-world, generally accepted identifier used to distinguish--that is uniquely identify -- real-world objects.  As its name implies, a () is familiar to end users and forms part of their day-to-day business vocabulary

    Natural Key or Natural Identiier

  14. A ( ) is a primary key created by the database designer to simplify the identification of entity instances. The () has no meaning in the user's environment--it exists only to distinguish one entity instane from another

    Surrogate Key

  15. () refer to data whose values change over time and for which you must keep a history of the data changes

    Time-Variant Data

  16. A ( ) occurs when a relationship is improperly or incompletely identified and is there therefore represented in a way that is not consistent with the real world.

    Design Trap

  17. A ( ) occurs when you have one entity in to 1:M relationships to other entities that is not expressed in the model

    Fan Trap

  18. ( ) is a process for evaluating and correcting table structures to minimize data redundancies, thereby reducing the likelihood of data anomalies. The ( ) process involves assigning attributes to tables based on the concept of determination

    Normalization

  19. ( ) produces a lower normal form; that is, a 3NF will be converted to a 2NF

    Denormalization

  20. ( ) exists when there is a functional dependence in which the determinant is only part of the primary key. For example, if (A,B) -> (C,D), B -> C, and (A,B) is the primary key, then the functional dependence B->C is a ( ) because only part of the primary key (B) is needed to determine the value of C.

    Partial Dependency

  21. A ( ) exists when there are functional dependencies such as X -> Y, Y -> Z, and X is the primary key

    Transitive Dependency

  22. A ( ) derives its name from the fact that a group of multiple entries of the same type can exist

    Repeating Group

  23. A ( ) diagram that depicts all dependencies found within a given table structure

    Dependency

  24. The term ( ) describes the tabular format in which:

    • - All of the key attributes are defines
    • - There are no repeating groups in the table
    • - Each row/column intersection contains one and only one value, not a set of values
    • - All atributes are dependent

  25. A ( ) is any attribute whose value dependency, write a copy of its determinant other values within a row

    Determinant

  26. A table is in ( ) when: 
    - It is 2NF
    and
    - It contains no transitive dependencies

    Third Normal Form (3NF)

  27. An ( ) is one that cannot be further subdivided

    Atomic Attribute

  28. ( ) refers to the level of detail represented by the values stored in a table's row.

    Granularity

  29. A table is in ( ) when every determinate in the table is a candidate key.

    Boyce-Codd normal form (BCNF)

  30. ( ) are a brief, precise and unambiguous description of a policy, procedure, or principle within a specific organization.
    - Sometimes misnamed

    Business Rules

  31. Anything about which data are to be collected and stored
    - Person, Place, Thing, or Event

    Entities

  32. Association among entities
    - ( ) between customer and agent
    - Short hand notation 1:1, 1:M, M:N

    Relationships

  33. Data Model/Database Model

    • - Iterative progressive process
    • - Level of detailed increases as understanding of problem domain increases
    • - When done properly data model is "blueprint" containing all instructions to build database to meet end-user needs

  34. Data models can facilitate interaction among the following:

    • - Designer
    • - Application programmer
    • - End User

  35. Characteristics of an entity
    - Customer entity has customer last name, customer first name

    Attributes

  36. - Restrictions placed on data
    - Help to ensure data entities
    - Expressed in form of rules

    Constraints

  37. Business rules set the stage for proper identification

    • - Identification 
    • - Attributes 
    • - Relationship
    • - Constraints

  38. Naming Conventions

    • - Identification process
    • - Attributes
    • - Relationships
    • - Constraints

  39. First Data Model

    • - 1960 - 1970
    • - VMS/VSAM
    • - Used mainly on an IBM mainframe

  40. Second Data Model

    • - 1970s
    • - Hierarchal and network
    •        - IMS, ADABAS, IDS-II
    •        - Early database system navigational           access

  41. Third Data Model

    • - Mid 1970s to Present
    • - Relational
    •     a. DB2, Oracle, MS SQL-Server, MySQL
    •     b. Conceptual simplicity
    •     c. ER modeling and support for relational    data modeling

  42. Fourth Data Model

    • Mid-1080s to present
    • - Object-oriented/relational (O/R)
    • - Star Schema support for data warehousing
    • - Web databases become common

  43. Next Generation Hierarchal

    • Present to Future
    • 1. Developed in 1960s to manage large amounts of data for manufacturing projects
    • 2. Structure represented by an upside down tree
    • 3. Contains levels or segments
    • 4. Segment equivalent to file system's record type
    • 5. 1:M type relationship in this model (typically)

  44. Next Generation Network

    • 1. Created to represent complex data relationships more effectively than hierarchal 
    • a. Improves database performance
    • b. Imposes a database standard
    • c. Record can have more than one parent

  45. Schema

    Conceptual organizational of entire database

  46. SubSchema

    Defines portion of the database seen by application programs that actually produce the desired information from data contained within database

  47. DML

    Defines the environment in which data can be managed and to work with data in database

  48. DDL

    Enables database administrator to define the schema components

  49. Relational Model

    • - Matrix composed of intersecting rows and columns
    • 1. Row - tuple
    • 2. Column - attribute

  50. Relational Diagram

    • 1. Representation of
    • a. relational database's entities
    • b. attributes within those entities
    • c. relationship between entities

  51. Relational Table

    • 1. Stores collection of related entities
    • 2. Resemble a file
    • 3. Difference between table and file
    •       a. table yields complete data and structural independence
    •            i. purely logical structure

  52. Reasons for Relational data models

    • a. Powerful and flexible query language
    •     i. SQL - allows user to specify what needs to be done without specifying how it must be done

  53. Three parts do SQL-based relational database application

    • i. End-user interface
    •    1. Allows user to interact with data
    • ii. Collection of tables stored
    •    1. Data perceived to be stored in tables
    • iii. SQL engine
    •    1. Executes all the queries or data requests

  54. Entity Relationship Model (ERM0

    • i. Graphical tool in which entities and their relationships are pictured
    • ii. Widely accepted standard for data modeling
    • iii. Peter Chen (1976) introduces Entity Relationship Diagram (ERD)

  55. Entity Relationship Diagram

    • - Peter Chen (1976)
    • 1. Connectivities written next to each entity box
    • 2. Relationships represented by a diamond connected to the related entities through the relationship line
    • 3. Complemented the relational data model concepts
    • 4. Row is known as entity instance or entity occurrence
    • 5. ER models represented by entity relationship diagrams (ERD)
    • 6. Entity represented by rectangle
    • 7. Connectivity labels relationship type
    • 8. Relationships describe association among data
    • 9. Connectivity labels relationship type
    • 10. Name of relationship is usually an active or passive verb

  56. Crow's Foot Notation

    • 1. Derived from three-pronged symbol used to represent "many" side of relationship
    • 2. Connectivity represented by symbols

  57. Object-Oriented Model

    • 1. Data and their relationships contained in single structure known as object
    • 2. Reflects different way to define and use entities
    • 3. Object contains all operations that can be performed on it
    • 4. Object is self-contained

  58. OO Data model based on following components

    • 1. Object is abstraction of real-world entity
    • 2. Attributes describe the properties of object
    • 3. Objects that share similar characteristics are grouped in classes

  59. UML - Unified Modeling Language

    - Unified Modeling Language

  60. Overlapping subtypes are subtypes that contain a unique subset of the supertype entity set

    False

  61. Specialization is the top-down process of identifying lower-level, more specific entity subtypes from a higher-level entity supertype

    True

  62. To model time-variant data, you must create a new entity in a M:N relationship with the original entity

    False.  It is a 1:M relationship

  63. A design trap occurs when a relationship is improperly or incompletely identified and is therefore represented in a way that is not consistent with the real world

    True

  64. Some designs use redundant relationships as a way to simplify the design

    False

  65. blank is a generic entity type that is related to one or more entity subtypes

    Entity Supertype

  66. The ( ) depicts the arrangement of higher-level entity supertypes (parent entities) and lower level entity subtypes (child entities).

    Specialization Hierarchies

  67. Within a specialization hierarchy, every subtype can have blank supertype(s) to which it is directly related.

    One or More

  68. The property of blank enables an entity subtype to inherit the attributes and relationships of the supertype

    Inheritance

  69. The default comparison condition for the subtype discriminator attribute is the blank comparison

    Equality

  70. Overlapping subtypes are subtypes that contain ( ) subsets of the supertype entity set

    Nonunique

  71. ( ) is the bottom-up process of identifying a higher-level, more generic entity supertype from lower-level entity subtypes.

    Generalization

  72. An entity cluster is formed by combining multiple interrelated entities into ( )

    Single Abstract Entity Object

  73. The ( ) characteristic of a primary key states that: The PK should not have embedded semantic meaning.  An attribute with embedded semantic meaning is probably better used as a descriptive characteristic of the entity rather than as an identifier

    Nonintelligent

  74. Composite primary keys are particularly useful as identifiers of composite entities, where each primary key is allowed only once in the ( ) relationship.

    M:N

  75. Normalization works through a series of stages called normal forms

  76. Normalization is a very important database design ingredient and the highest level is always the most desirable

  77. All relational tables satisfy the 1NF requirements

  78. Converting a database format from 1NF to 2NF is a complex process

  79. It is possible for a table in 2NF to exhbit transitive dependency, where one or more nonprime attributes functionally determine other nonprime attributes

  80. The combination of normalization and ER modeling yields a useful ERD, whose entities my now be translated into appropriate relationship structures

  81. The advantage of higher processing speed must be carefully weighed against the disadvantage of data anomalies

  82. Normalization purity is easy to sustain in the modern database enviroment

  83. Unnormalized database tables often lead to various data redundancy disasters in production databases.

  84. 1NF, 2NF, and 3NF are ( )

  85. Some very specialized applications may require normalization beyond the ( )

  86. A relational table must not contain a()

  87. If you have three different transitive dependencies, ( ) different determinant(s) exist

  88. Before converting a table into 3NF, it is imperative that the table already be in ( )

  89. The most likely data type for a surrogate key is ( )

  90. From a strictly database point of view, ( ) attribute values can be calculated when they are needed to write reports or invoices

  91. A table where all attributes are dependent on the primary key and are independent on the primary key and are independent of each other, an no row contains two or more multivalued facts about an entity, is said to be in ( )

  92. When designing a database, you should ( )

  93. Systems analysis is used to determine the need for an information system and to establish to limits

  94. The primary objective in database design is to create complete, denormalized, redundant, and fully integrated conceptual, logical, and physical database models

  95. The SDLC's planning phase yields a general overview of the company and its objectives.

  96. Problems defined during the planning phase are examined in greater detail during the analysis phase

  97. During the testing phase, the system is subjected to exhaustive testing until it is ready for use

  98. Because every request for structural changes requires retracing the SDLC steps, the system is always at some stage of the SDLC

  99. To analyze the company situation, the database designer must discover what the company's operational components are, how they interact

  100. The testing and evaluation phase occurs after applications programming

  101. After the initial declarations in a study, the database designer must carefully probe in order to generate additional information that will help define the problem within the larger framework of company operations

  102. The testing and evaluation phase occurs after applications programming

  103. Performance evaluation is rendered more difficult by the fact that there are standard measurements for database performance

  104. Coding, testing, and debugging are part of the  ( ) phase of the SDLC

  105. Installation and fine tuning are part of the ( ) phase of the SDLC

  106. Evaluation, maintenance, and enhancement are part of the ( ) phase of the SDLC

  107. The SDLC is most important to the ( )

  108. What are the requirements of the current system's end user? is a question asked during the ( ) phase of the SDLC

  109. Producing the required information flow is part of the ( ) phase of the DBLC

  110. The implementation and loading phase of the DBLC involves ( )

  111. Once the data has been loaded into the database, the ( ) tests and fine-tunes the database for performance, integrity, concurrent access, and security constraints.

  112. The first step in developing the conceptual model using ER diagrams is to ( )

  113. The ( ) design is the process of selecting the data storage data access characteristics of the database.

Are subtypes that contain Nonunique subsets of the supertype entity set?

Disjoint subtypes are subtypes that contain nonunique subsets of the supertype entity set.

Can a subtype have more than one supertype?

A supertype can have one or more subtypes, and a subtype can have one or more supertypes. A supertype can be a subtype of some other supertype, and a subtype can be a supertype of some other subtype.

What is an overlapping subtype give an example?

An example of an overlapping subtype structure would be the classification of employees at a College into instructors and administrators. Since some instructors are likely to be administrators, this would be an overlapping subtype structure. Hence, we would have EMPLOYEE as a supertype of INSTRUCTOR and ADMINISTRATOR.
However, a subtype is (directly) a subtype of only one supertype. Thus, the use of supertypes and subtypes in ERDs resembles the use of ``single inheritance'' between classes, in object-oriented programming.