© the mcgraw-hill companies, all rights reserved appendix c designing databases appendix c...
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© The McGraw-Hill Companies, All Rights Reserved
APPENDIX C
DESIGNING DATABASES
APPENDIX C
DESIGNING DATABASES
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INTRODUCTION
The 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 Relationships
The 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-Many
Many-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 ORDERAn 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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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 TABLES
A unique primary key makes it possible to uniquely identify every row in a table
The 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