Relational Databases
HSC IPT
Introduction
There are two types of database: Flat file
and Relational.
 The database you created is flat
because all the data is lumped together
in one table and some duplication does
occur.
 Relational databases use a series of
related tables which helps reduce
redundant data.
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New Terms
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ATTRIBUTE – the defined property of an entity.
Attributes are the same as fields in a flat file database.
FOREIGN KEY – an attribute which is the primary key
of another table.
DATA REDUNDANCY – where the same data is stored
in two or more records or files. This is undesirables
duplication of data that takes up valuable space.
RELATIONSHIP – the way in which entities are related
to each other. The Key Field is used to link entities.
Relational Databases
Every record has a PRIMARY KEY FIELD
or a unique combination of fields forming a
COMPOUND KEY.
 Data redundancy is reduced as the same
data is not scattered around numerous
files.
 All data is stored in tables.
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Types of Relationships
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ONE TO ONE - each record in the first entity (ie table) is
related to exactly one record in the second entity. For
example each primary teacher is assigned to one class
in the primary school.
ONE TO MANY - each record in the first entity relates to
many records in the second entity. For example, each
secondary teacher is assigned to many classes in the
high school.
MANY TO MANY – each record in the first entity relates
to many records in the second entity, and each record in
the second entity is related to many records in the first
entity. For example, each student studies many subjects
and each subject is studied by many students.
Schema
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SCHEMA is an organised plan of the
entire database. It shows where the data
is found and the logical relationships.
CUSTOMER
CustomerID
FirstName
LastName
Address
State
Postcode
SALESPERSONS
SalespersonId
FirstName
LastName
WorkPhone
HireDate
ORDERS
OrderID
CustomerID
OrderDate
SalespersonID
OrderPaid
ORDER DETAILS
OrderID
ProductID
Quantity
PRODUCTS
ProductID
ProductName
UnitsInStock
UnitsOnOrder
UnitPrice
Normalisation of Data
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Normalisation of data is the process of analysing data to
create the most efficient database structure.
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The most important procedure in normalisation is to
eliminate data redundancy by removing the repeating
fields and regrouping them as a new record.
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It involves dividing a database into two or more tables
and defining relationships between the tables.
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There are three main normal forms.
First Normal Form
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1NF: Each field in a table contains
different information. For example, in an
employee list, each table would contain
only one date of birth field.
Second Normal Form
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2NF: No field values can be derived
from another field. For example, if a
table already included a date of birth
field, it could not also include a birth year
field, as this information would be
redundant.
Third Normal Form
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3NF: No duplicate information is
permitted. For example, if two tables
both require a date of birth field, the
date of birth information would be
placed into a separate table, and the
two other tables would then access
the information via an index field in the
date of birth table.
Questions
What’s the difference between a flat file
database and a relational database?
 What is data redundancy?
 How does a relational database eliminate
data redundancy?
 What are the three types of relationships?
 What is a schema?
 What is meant by normalisation of data?
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Homework
What 3 tables would you need?
 What fields would you need in these
tables?
 Start planning/thinking about this over
the weekend.
 Have a go at drawing a schema!!
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