APPENDIX C

DESIGNING DATABASES

APPENDIX C

DESIGNING DATABASES

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INTRODUCTIONThe core chapters introduced:

– Database - maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)

– Database management system (DBMS) – creates, reads, updates, and deletes data in a database while controlling access and security

– Relational database model - a type of database that stores its information in the form of logically-related two-dimensional tables

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ENTITIES AND DATA RELATIONSHIPS

Data model – The logical data structures that detail the relationships among data elements using graphics or pictures

The underlying relationships in a database environment are:

– Independent of the data model

– Independent of the DBMS that is being used

Entity-relationship diagram (ERD) - A technique for documenting the relationships between entities in a database environment

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Entities And Their Attributes

Entity - Also called a table, stores information about a person, place, thing, transaction, or event

– A customer is an entity, as is a merchandise item

Attribute – Data elements associated with an entity

A CUSTOMER entity can be described by a Customer Number, First Name, Last Name, Street, City, State, Zip Code, Phone Number

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Entities And Their Attributes

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Attributes

There are several types of attributes including:

– Simple versus composite

– Single-valued versus multi-valued

– Stored versus derived

– Null-valued

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Simple versus Composite

Composite attributes can be divided into smaller subparts, which represent more basic attributes that have their own meanings

Example: Address Address can be broken down into a number of subparts, such

as Street, City, State, Zip Code

Street may be further broken down by Number, Street Name, and Apartment/Unit Number

Attributes that are not divisible into subparts are called simple attributes

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Simple versus Composite

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Single-Valued versus Multi-Valued

Single-valued attribute means having only a single value of each attribute of an entity at any given time

Example:– A CUSTOMER entity allows only one

Telephone Number for each CUSTOMER– If a CUSTOMER has more than one Phone

Number and wants them all included in the database the CUSTOMER entity cannot handle them

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Multi-valued attribute means having the potential to contain more than one value for an attribute at any given time

An entity in a relational database cannot have multi-valued attributes, those attributes must be handled by creating another entity to hold them

Relational databases do not allow multi-valued attributes because they can cause problems: – Confuses the meaning of data in the database– Significantly slow down searching– Place unnecessary restrictions on the amount of data

that can be stored

Single-Valued versus Multi-Valued

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Single-Valued versus Multi-Valued

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Stored versus Derived If an attribute can be calculated using the value of

another attribute, it is called a derived attribute

The attribute that is used to derive the attribute is called a stored attribute

Derived attributes are not stored in the file, but can be derived when needed from the stored attributes

Example: A person’s age - if the database has a stored attribute such as the person’s Date of Birth, you can create a derived attribute called Age from taking the Current Date and subtracting the Date of Birth to get the age

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Null-Valued

Null-valued attribute – Assigned to an attribute when no other value applies or when a value is unknown

Example: A person who does not have a mobile phone would have null stored at the value for the Mobile Phone Number attribute

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DOCUMENTING ENTITY-RELATIONSHIP DIAGRAMS

The two most commonly used styles of ERD notation are:1. Chen

2. Information Engineering

The Chen model uses rectangles to represent entities – Each entity's name appears in the rectangle

and is expressed in the singular, as in CUSTOMER

– Attributes are expressed in ovals

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Basic Data Relationships

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Basic Data RelationshipsThe relationships that are stored in a database

are between instances of entities

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Once the basic entities and attributes have been defined, the next task is to identify the relationships among entities

There are three basic types of relationships:

1. One-to-one

2. One-to-many

3. Many-to-many

Basic Data Relationships

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One-to-One

One-to-one (1:1) – A relationship between two entities in which an instance of entity A can be related to only one instance of entity B and entity B can be related to only one instance of entity A

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One-to-ManyOne-to-many (1:M) – A relationship between two

entities, in which an instance of entity A, can be related to zero, one, or more instances of entity B and entity B can be related to only one instance of entity A

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Many-to-ManyMany-to-many (M:N) – A relationship

between two entities in which an instance of entity A can be related to zero, one, or more instances of entity B and entity B can be related to zero, one, or more instances of entity A

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Documenting Relationships – The Chen Method

The Chen method uses diamonds for relationships and lines with arrows to show the type of relationship between entities

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There is no obvious way to indicate weak entities and mandatory relationships– An ORDER should not exist in the database without

a CUSTOMER– ORDER is a weak entity and its relationship with a

CUSTOMER is mandatory– Some database designers have added a new symbol

to the Chen method for a weak entity, a double-bordered rectangle

Documenting Relationships – The Chen Method

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DEALING WITH MANY-TO-MANY RELATIONSHIPS

There are problems with many-to-many relationships1.The relational data model cannot handle

many-to-many relationships directly – It is limited to one-to-one and one-to-many

relationships– Many-to-many relationships need to be replaced

with a collection of one-to-many relationships

2.Relationships cannot have attributes– An entity must represent the relationship

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Composite Entities

Composite entities - Entities that exist to represent the relationship between two other entities

Example:

– There is a many-to-many relationship between an ITEM and an ORDER An ORDER can contain many ITEM(s) and over

time, the same ITEM can appear on many ORDER(s)

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Composite Entities

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Composite Entities

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RELATIONSHIP CONNECTIVITY AND CARDINALITY

Cardinality - expresses the specific number of entity occurrences associated with one occurrence of the related entity

In the Chen model, the cardinality is indicated by placing numbers beside the entities in the format of (x, y)– The first number is the minimum value and the second

number is the maximum value

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Relational Data Model and the Database

Once the ERD is completed, it can be translated from a conceptual logical schema into the formal data model required by the DBMS

Most database installations are based on the relational data model

The relational data model is the result of the work of one person, Edgar (E. F.) Codd

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FROM ENTITIES TO TABLES

The word “table” is used synonymously with “entity”

The definition specifies what will be contained in each column of the table, but does not include data

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FROM ENTITIES TO TABLES

When rows of data are included, an instance of a relation is created

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FROM ENTITIES TO TABLES

When the same column name appears in more than one table and tables that contain that column are used in the same data manipulation operation

– The name of the column must be qualified by preceding it with the name of the table and a period

Example:

– CUSTOMER.Customer Number, First Name, Last Name, Phone Number

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FROM ENTITIES TO TABLES

A row in a relation has the following properties:– Only one value at the intersection of a

column and row - a relation does not allow multi-valued attributes

– Uniqueness - there are no duplicate rows in a relation

– Primary key - A field (or group of fields) that uniquely identifies a given entity in a table

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FROM ENTITIES TO TABLESA unique primary key makes it possible to

uniquely identify every row in a tableThe primary key is important to define to be able

to retrieve every single piece of data put into a database

There are only three pieces of information to retrieve for any specific bit of data:1. The name of the table

2. The name of the column

3. The primary key of the row

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The proper notation to use when documenting the name of the table, the column name, and primary key:– CUSTOMER(Customer Number, First Name,

Last Name, Phone Number) Two qualities of all primary keys:

1. A primary key should contain some value that is highly unlikely ever to be null

2. A primary key should never change

FROM ENTITIES TO TABLES

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LOGICALLY RELATING TABLES

The use of identifiers represent relationships between entities

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When a table contains a column that is the same as the primary key of a table, the column is called a foreign key

Foreign key - A primary key of one table that appears as an attribute in another file and acts to provide a logical relationship between the two files

Example:– CUSTOMER(Customer Number, First Name, Last Name, Phone

Number)

– ORDER(Order Number, Customer Number, Order Date)

LOGICALLY RELATING TABLES

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LOGICALLY RELATING TABLES

Foreign keys do not necessarily need to reference a primary key in a different table

– They need only reference a primary key

Example:

– EMPLOYEE(Employee Number, First Name, Last Name, Department, Manager Number)