Data Modeling 2

occurrence

analogous to a row in the relational table

Planning

defines the goals of the database , explains why the goals are important, and sets out the path by which the goals will be reached

Existence

denotes whether the existence of an entity instance is dependent upon the existence of another, related, entity instance defined as either mandatory or optional

Attributes

describe the entity of which they are associated; classified as identifiers or descriptors

descriptor

describes a non-unique characteristic of an entity instance.

connectivity of a relationship

describes the mapping of associated entity instances in the relationship. The values of connectivity are "one" or "many".

Information needed for the requirements analysis

review of existing documents interviews with end users review of existing automated systems

methods used to create a data model

the Entity-Relationship (ER) approach and the Object Model

Steps In Building the Data Model

1. Identification of data objects and relationships 2. Drafting the initial ER diagram with entities and relationships 3. Refining the ER diagram 4. Add key attributes to the diagram 5. Adding non-key attributes 6. Diagramming Generalization Hierarchies 7. Validating the model through normalization 8. Adding business and integrity rules to the Model

Three points to keep in mind during the requirements analysis

1. Talk to the end users about their data in "real-world" terms. 2. Take the time to learn the basics about the organization and its activities that you want to model. 3. End-users typically think about and view data in different ways according to their function within an organization.

ER diagram notations

Bachman, crow's foot, and IDEFIX represent entities as rectangular boxes and relationships as lines connecting boxes. Each style uses a special set of symbols to represent the cardinality of a connection.

generalization hierarchy

a form of abstraction that specifies that two or more entities that share common attributes can be generalized into a higher level entity type called a supertype or generic entity

Associative entities (also known as intersection entities)

are entities used to associate two or more entities in order to reconcile a many-to-many relationship.

Entities

are the principal data object about which information is to be collected; usually recognizable concepts, either concrete or abstract, such as person, places, things, or events which have relevance to the database; classified as independent or dependent

effective data model

completely and accurately represents the data requirements of the end users. It is simple enough to be understood by the end user yet detailed enough to be used by a database designer to build the database. The model eliminates redundant data, it is independent of any hardware and software constraints, and can be adapted to changing requirements with a minimum of effort.

Data Model

conceptual representation of the data structures that are required by a database. The data structures include the data objects, the associations between data objects, and the rules which govern operations on the objects (equivalent to an architect's building plans.)

Components of A Data Model

data model gets its inputs from the planning and analysis stage. The data model has two outputs. The first is an entity-relationship diagram which represents the data strucures in a pictorial form. The second component is a data document. This a document that describes in detail the data objects, relationships, and rules required by the database

Database design

design the logical and physical structure of one or more databases to accommodate the information needs of the users in an organization for a defined set of applications". The design process roughly follows five steps: 1. planning and analysis 2. conceptual design 3. logical design 4. physical design 5. implementation

Subtypes

either mutually exclusive (disjoint) or overlapping (inclusive

ER Notation

entities are represented by labeled rectangles. The label is the name of the entity. Entity names should be singular nouns. * relationships are represented by a solid line connecting two entities. The name of the relationship is written above the line. Relationship names should be verbs. * attributes, when included, are listed inside the entity rectangle. Attributes which are identifiers are underlined. Attribute names should be singular nouns. * cardinality of many is represented by a line ending in a crow's foot. If the crow's foot is omitted, the cardinality is one. * existence is represented by placing a circle or a perpendicular bar on the line. Mandatory existence is shown by the bar (looks like a 1) next to the entity for an instance is required. Optional existence is shown by placing a circle next to the entity that is optional

data model

focuses on what data should be stored in the database while the functional model deals with how the data is processed; used to design the relational tables

direction of a relationship

indicates the originating entity of a binary relationship. The entity from which a relationship originates is the parent entity; the entity where the relationship terminates is the child entity. determined by its connectivity

Analysis

involves determining the requirements of the database. This is typically done by examining existing documentation and interviewing users.

ternary relationship

involves three entities and is used when a binary relationship is inadequate.; decomposed into two or more binary relationships

entity occurrence(also called an instance)

is an individual occurrence of an entity

cardinality of a relationship

is the actual number of related occurences for each of the two entities. The basic types of connectivity for relations are: one-to-one, one-to-many, and many-to-many.

Degree of a Relationship

is the number of entities associated with the relationship

goal of the data model

is to make sure that the all data objects required by the database are completely and accurately represented; detailed enough to be used by the database developers to use as a "blueprint" for building the physical database

requirements analysis

is usually done at the same time as the data modeling

Identifiers

more commonly called keys, uniquely identify an instance of an entity

Entity-Relation Model (ER

most common method used to build data models for relational databases; easily be transformed into relational tables; simple and easy to understand; e used as a design plan by the database developer to implement a data model in a specific database management software.

Data modeling

must be preceded by planning and analysis

Generalization

occurs when two or more entities represent categories of the same realworld object

non-identifying relationship

one in which both entities are independent

identifying relationship

one in which one of the child entities is also a dependent entity.

independent entity

one that does not rely on another for identification

dependent entity

one that relies on another for identification.

Relationships

represents an association between two or more entities. An example of a relationship would be: employees are assigned to projects projects have subtasks departments manage one or more projects classified by their degree, connectivity, cardinality, direction, type, and existence

many-to-many (M:N) relationship

sometimes called non-specific, is when for one instance of entity A, there are zero, one, or many instances of entity B and for one instance of entity B there are zero, one, or many instances of entity A. An example is: employees can be assigned to no more than two projects at the same time; projects must have assigned at least three employees

Binary relationships

the association between two entities is the most common type in the real world. ( "some employees are married to other employees".)

goals of the requirements analysis

to determine the data requirements of the database in terms of primitive objects * to classify and describe the information about these objects * to identify and classify the relationships among the objects * to determine the types of transactions that will be executed on the database and the interactions between the data and the transactions * to identify rules governing the integrity of the data

Subtypes entities

used in generalization hierarchies to represent a subset of instances of their parent entity, called the supertype, but which have attributes or relationships that apply only to the subset.

ER model

views the real world as a construct of entities and association between entities.

mutually exclusive category

when an entity instance can be in only one category

overlapping category

when an entity instance may be in two or more subtypes

one-to-one (1:1) relationship

when at most one instance of a entity A is associated with one instance of entity B. For example, "employees in the company are each assigned their own office. For each employee there exists a unique office and for each office there exists a unique employee.

one-to-many (1:N) relationships

when for one instance of entity A, there are zero, one, or many instances of entity B, but for one instance of entity B, there is only one instance of entity A. An example of a 1:N relationships is a department has many employees each employee is assigned to one department

information contained in the data model

will be used to define the relational tables, primary and foreign keys, stored procedures, and triggers