DBSQL 4-1 Copyright © Genetic Computer School 2009 Chapter 4 Database Design.

Copyright © Genetic Computer School 2009DBSQL 4-1

Chapter 4

Database Design

Copyright © Genetic Computer School, Singapore 2009

DBSQL 4-2

Chapter 4 Overview

Database DesignRedundancy IssuesData AnomalyFunctional Dependency TheoryNormalizationDrawbacks of NormalizationDenormalization


DBSQL 4-3

Database DesignDBMS

is a program or a collection of programs, through which users interact with a database

is a software system that enables users to define, create and maintain the database and which provides controlled access to this database.


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Cont’

Database Processing

Data entryand reports

Data entryand reports

DBMS

Property, Owner, Renter

and Lease details

+ File definitions

Database


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Database Development Process

PLANNING

Enterprise Data Model

Conceptual Data Model

Logical Data Model

Physical Data Model

Database and Repositories

IMPLEMENTATION

PHYSICAL DATABASEDESIGN

LOGICAL DATABASEDESIGN

ANALYSIS


DBSQL 4-6

Redundancy Issues

Redundancy is the common problem when implementing a database. It means that duplication of data exists and the same data are stored in more than one place. If those redundant data are to be removed then it is possible that data might be lost, further data complications and problems may lead to anomalies. There are three pre-defined anomalies existing: insertion, deletion and updating of data.


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Data anomalies

Insert Delete Update


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Functional Dependencies

The functional dependency occurs when one attribute in a relation uniquely identifies another attribute. It can be denoted as ‘AB’ which means that ‘B is functionally dependent upon A’.


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Cont’

A B It means:

B is functionally dependent on AA determines BA is called determinant

B is called object of the determinant


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FD Inference Rules

Subset Property Augmentation Transitivity

Secondary rules Union Decomposition Pseudo-transitivity


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Types of Dependency

Functional

Partial

Transitive

It is a candidate key that uniquely identifies a relation

This is the situation that exists if it is necessary to only use a subset of the attributes of the composite determinant to identify its object.

A transitive dependency exists when there is an intermediate functional dependency. If AB, BC and if AC then it can be stated that the transitive dependency exists.


DBSQL 4-12

Normalization

Is a formal technique for analyzing relations based on their primary key (or candidate keys in the case of BCNF) and functional dependencies.

Normalization is often executed as a series of steps. Each step corresponds to a specific normal form, which has known properties.


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Cont’

The technique involves a series of rules that can be tested against individual relations so that a database can be normalized to any degree.


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Stages of Normalization Process


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First Normal Form (1NF)

A table is said to be in First Normal Formal if it only contains one and only one atomic value. In this stage repeating groups will also be eliminated. Removing repeating groups is the starting point in the quest to create tables that are as free of problems as possible. Tables without repeating groups are said to be in its First Normal Form (1NF).


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Example

Orders (OrderNum, OrderDate, (PartNum, NumOrdered))

Orders

OrderNum OrderDate PartNum NumOrdered

21608 10/20/2008 AT94 11

DR93 1

DW11 1

21613 10/21/2008 KL62 4

21614 10/21/2008 KT03 2

BV06 2

CD52 4

21619 10/24/2008 DR93 1

21623 10/25/2008 KV29 2

10/20/200821610

10/23/200821617


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Second Normal Form (2NF)

To convert a table into its Second Normal Form, it should first be in its First Normal Form (1NF). A table is said to be in its Second Normal Form if all of its non-key attributes only depends on one key attribute meaning no partial dependencies


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ExampleOrders

OrderNum OrderDate PartNum Description NumOrdered Quoted Price

21608 10/20/2008 AT94 Table 11 100.00$

21610 10/20/2008 DR93 Computer 1 925.00$

21610 10/20/2008 DW11 Chair 1 21.00$

21613 10/21/2008 KL62 Notebook 4 5.00$

21614 10/21/2008 KT03 Aircon 2 1,500.00$

21617 10/23/2008 BV06 TV 2 2,101.00$

21617 10/23/2008 CD52 Microwave Oven 4 794.00$

21619 10/24/2008 DR93 Computer 1 200.00$

21623 10/25/2008 KV29 Fax Machine 2 350.00$

Orders (OrderNum, OrderDate, PartNum, Description, NumOrdered, QuotedPrice)


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Cont’

Orders (OrderNum, OrderDate)

Part (PartNum, Description)

OrderLine (OrderNum, PartNum, NumOrdered, QuotedPrice)

Part (PartNum, Description)

OrderLine (OrderNum, PartNum, NumOrdered, QuotedPrice)


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Third Normal Form (3NF)

The general concept of Third Normal Form (3NF) is to remove transitive dependencies.


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Example

Customer (CustID, CustName, CustAddress, Balance,CustCreditLimit, CustStatus, RepNo, FirstName, LastName)

Representative (RepNo, FirstName, LastName)

Customer (CustID, CustName, CustAddress, Balance,CustCreditLimit, CustStatus, RepNo)


DBSQL 4-22

Boyce Codd Normal Form (BCNF)

A relation is in BCNF, if for every non-trivial functional dependency XA, X is a super key. In other words a relation is in BCNF, if and only if the determinant is a candidate key.

BCNF is a stronger form of normalization than 3NF, which eliminates the first rule of 3NF, which allows the right side of the functional dependency to be a prime attribute.


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Fourth Normal Form (4NF)

A table is in fourth normal form (4NF) when it is third normal form (3NF) and there are no multi-valued dependencies.

Multi-valued dependencies

A B


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Fifth Normal Form

The goal of the Fifth Normal Form is to remove join dependency. In normalizing a relation seldom it would reach to this stage.


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Drawbacks of Normalization

It produces a lot of tables Might slow the performance when querying data at multiple tables Query becomes complex


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Denormalization

Denormalization is used primarily to improve performance in cases where a database and the relation itself are over normalized causing an overhead to the query processor.


DBSQL 4-27

End

DBSQL 4-1 Copyright © Genetic Computer School 2009 Chapter 4 Database Design.

Documents

database design slide

determinant slide

update slide

cont database processing

data anomalies

determinant b

database design dbms

transitive dependency