NORMALIZATION Part 1: The Concept 1. Objectives 2 How to undertake the normalization process. How normalization uses functional dependencies to group

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NORMALIZATIONPart 1: The

Concept

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Objectives How to undertake the normalization process. How normalization uses functional dependencies to

group attributes into relations that are in a known normal form.

How to identify the most commonly used normal forms: First Normal Form (1NF) Second Normal Form (2NF) Third Normal Form (3NF)

The problems associated with relations that break the rules of 1NF, 2NF, or 3NF.

How to represent attributes shown on a form as 3NF relations using normalization.

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Introduction

2 strategies in creating data model: We have adopted a top-down approach to

database design that begins by identifying the entities and relationship.

Normalization is a bottom-up approach to database design that begins by examining the relationships between attributes.

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Database Design Strategies

Two classical approaches/strategies to dB design:

Conceptual Model

Entity

Attribute Attribute

Entity

Attribute Attribute

Top-down Bottom-up{ Normalization }

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Table & Relational Schema

staffNO sName position salary branchNO

S21 Johan Manager 3000 B005

S37 Ana Assistant 1200 B003

S14 Daud Supervisor 1800 B003

S9 Mary Assistant 900 B007

S5 Siti Manager 2400 B003

S41 Jani Assistant 900 B005

branchNO bAddress

B005 123, Kepong

B007 456, Nilai

B003 789, PTP

staff branch

staff (staffNO, sName, position, salary, *branchNO)

branch (branchNO, bAddress)

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Normalization

When we design a database, the main objective is to create an accurate representation of data, relationship between the data, and constraints on the data that is relevant.

To achieve this objective, we have to identify suitable set of relations (table) by creating good table structure/process of assigning attributes to entities. The process is known as Normalization. Process for evaluating and correcting table

structures to minimize/control data redundancies {reduces data anomalies}.

Works through a series of stages called normal forms.

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NormalizationThe most commonly used normal forms:

First Normal Form(1NF) Second Normal Form (2NF) Third Normal Form (3NF)

1NF < 2NF < 3NF

Highest normalization is not always desirableMore JOINS are requiredAffect data retrieval performance/high response

time For most business database design purposes, 3NF

is as high as we need to go in normalization process

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Normalization Every normal form is based on functional

dependencies between attributes in a relationship.

Each relationship can be normalized into a specific form to avoid anomalies. Anomalies?

Anomaly = abnormality Ideally a field value change, should be made

only in a single place. Data redundancy, promotes an abnormal

condition by forcing field value changes in many different locations.

Insertion anomalies Deletion anomalies Modification/Update anomalies

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Functional Dependencies

An important concept associated with normalization is functional dependency which describes the relationship between attributes.

In this section, you will learn about functional dependency and then focus on the particular characteristics of functional dependency that are useful for normalization.

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Functional dependency can be divided into two types: Full functional dependency/Partial

dependency (PD) Will be used to transform 1NF 2NF

Transitive dependency (TD) Will be used to transform 2NF 3NF

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Multivalued Attributes (or repeating groups): non-key attributes or groups of non-key attributes the values of which are not uniquely identified by (directly or indirectly) (not functionally dependent on) the value of the Primary Key (or its part).

1st row

2nd row

Relational SchemaSTUDENT(Stud_ID, Name, (Course_ID, Units))

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Partial Dependency – when an non-key attribute is determined by a part, but not the whole, of a COMPOSITE primary key (The Primary Key must be a Composite Key).

Cust_ID → Name

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Transitive Dependency – when a non-key attribute determines another non-key attribute.

Dept_ID → Dept_Name

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Consider a relation with attributes A and B, where attribute B is functionally depends on attribute A. Let say an A is a PK of R.

To describe the relationship between attributes A and B is to say that “A functionally determines B”.

A BB is functionallydepends on A

R(A,B)A B

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When a functional dependency exist, the attribute or group of attributes on the left-handed side of the arrow is called determinant.

Determinant:

Refers to the attributes, or a group of attributes, on the

left handed side of the arrow of a functional dependency.

A BA functionally

determines B

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staffNO sName position salary branchNo

S21 Johan Manager 3000 B005

S37 Ana Assistant 1200 B003

S14 Daud Supervisor 1800 B003

S9 Mary Assistant 900 B007

S5 Siti Manager 2400 B003

S41 Jani Assistant 900 B005

branchNO bAddress

B005 123, Kepong

B007 456, Nilai

B003 789, PTP

staff

branch


Determinant

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Functional Dependencies Consider the attributes staffNO and position of

the staff relation. For a specific staffNO (S21), we can determine

the position of that member of staff as Manager. staffNO functionally determines position.

Staff number (S21) Position (manager)

staffNO positionposition is functionally

depends on staffNO

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However the next figure illustrate that the opposite is not true, as position does not functionally determines staffNO.

A member of staff holds one position; however, they maybe several members of staff with the same position.

Position(manager)staff number (S21)

staff number (S5)

position staffNOstaffNO does not functionally

depends on position

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Partial Dependencies: Full functional dependency indicates that if A and B

are attributes of a relation, B is fully functionally dependent on A, if B is functionally dependent on A, but not on any proper subset of A.

staff(staffNO,sName,position,salary,branchNO)

staffNO, staffName branchNO

True!!! each value of (staffNO, sName) is associated with a single value of branchNO.

however, branchNO is also functionally dependent on staffNO.


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Transitive Dependencies:

staff(staffNO,sName,position,salary,*branchNO)branch(branchNO,bAddress)

staffNO sName,position,salary,branchNO,bAddress

branchNO bAddress

True for transitive dependency!!! branchNO → bAddress

exists on staffNO via branchNO


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Normalization Process

Formal technique for analyzing relations based on their Primary Key (or candidate keys) and functional dependencies.

The technique executed as a series of steps (stage). Each step corresponds to a specific normal form, that have specific characteristic.

As normalization proceeds, the relations become progressively more restricted (stronger) in format and also less vulnerable to anomalies.

Data Redundancies

0NF/UNF

1NF

2NF

3NF

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Relationship between Normalize FormDenormalization

Normalization

Figure 1: Diagrammatic illustration of the relationship between the normal forms

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Users Users’ requirements specification

Forms/reports that are used or generated

by the enterprise

Sources describing the enterprise such as data

dictionary and corporate data model

Unnormalized Form (UNF)

First Normal Form (1NF)

Second Normal Form (2NF)

Third Normal Form (3NF)

Transfer attributes into table format

Remove repeating group

Remove partial dependencies

Remove transitive dependencies

Data Sources

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2NF

3NF

UNF1)Repeat Group

2)PK is not defined

1NF1)Remove Repeat Group

2)Defined PK composite PK consist of attributes

Test for partial dependency

If (exist)

(1 Table)

Test for transitive dependency

If (exist)

(1 or 2 Tables)

(2 or 3 Tables)

(more then 1 table)

(3 or 4 Tables)

(a b …. TD) 1

(a ……. TD) 2

(b ….… TD) 3

(a, b x, y)

(a c, d)

(b z)

(c d)

Normalization Process Relation/Table Format

- Have repeating group-PK not defined

- No repeating group-PK defined-Test partial dependency

- No repeating group-PK defined-No partial dependency-Test transitive dependency

- No repeating group-PK defined-No partial dependency-No transitive dependency

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Remember this!!! Unnormalized (UNF): There are multivalued

attributes or repeating groups, not CK (or PKs) 1NF: NO multivalued attributes or repeating

groups, has CK (or PKs) 2NF: 1NF with NO Partial Dependencies (PD) 3NF: 2NF with NO Transitive Dependencies (TD)

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Unnormalized Form (UNF)

To create an unnormalized table Transform the data from the information

source (e.g. form) into table format with columns and rows.

Unnormalized Form = A table that contains one or more repeating UNF/0NF groups

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First Normal Form (1NF)

A relation is in 1NF if every attribute for every tuple have a value and domain for each attribute can not be simplified anymore.

First Normal Form = A relation in which the intersection of each row 1NF and column contains one and only one value.

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Transforming UNF to 1NF

STUDENT

Stud_ID Name Course_ID Units

101 Lennon MSI 250 3.00

101 Lennon MSI 415 3.00

125 Johnson MSI 331 3.00

STUDENT

Stud_ID Name Course_ID Units

101 Lennon MSI 250 3.00

MSI 415 3.00

125 Johnson MSI 331 3.00

UNF

1NF

To-do list:1. Remove

repeating groups

2. Identify Composite Key

1

2

3

2

1

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Example 1: Determine UNF

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UNF to 1NF

Nominate an attribute or group of attributes to act as the key for the unnormalized table.

Identify the repeating group(s) in the unnormalized table which repeats for the key attribute(s).

Step 1: Eliminate the Repeating Groups Eliminate nulls: each repeating group attribute

contains an appropriate data value Step 2: Identify the Primary Key

Must uniquely identify attribute value New key must be composed

Step 3: Identify All Dependencies Dependencies are depicted with a diagram

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UNF to 1NF

Relational Schema

STUDENT(Stud_ID, Name, (Course_ID, Units))

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UNF to 1NF

Key Attribute: Stud_ID, Course_IDRepeating Group: (Course_ID, Units)

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UNF to 1NF

Relational Schema

STUDENT(Stud_ID, Name, Course_ID, Units)

Ensure a single value at the intersection of each row and column Enter appropriate student data in each row

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UNF to 1NF

Key Attribute: Stud_ID, Course_IDRepeating Group: (Course_ID, Units)

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UNF to 1NF

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UNF to 1NF

Dependency diagram: Depicts all dependencies found within given

table structure Helpful in getting bird’s-eye view of all

relationships among table’s attributes Makes it less likely that you will overlook an

important dependency

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UNF to 1NF

Remove the repeating group by Entering appropriate data into the empty

columns of rows containing the repeating data Fill the blanks by duplicating the non

repeating data, where required. This approach is commonly referred to as

”flattening table”. This approach will produce redundancy in a

relationship, but it can be eliminated in higher normalization process.

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UNF to 1NF

Example: DreamHome Case Study

A collection of DreamHome leases (rent) form is shown in Figure 2. The lease on top is for a client called Rannia who is leasing a property in Skudai, Johor, which is owned by Dollah. For this worked example, we assume that a client rents a given property only once and cannot rent more than one property at any one time.

Sample data is taken from two leases for two different clients called Rannia and Ahmad and is transformed into table format with rows and columns, as shown in Figure 3. This is an example of unnormalized table.

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UNF to 1NF

AlamatRumah

MulaSewa

TamatSewa

HargaSewa

NoPemilik

Nama Pemilik

PG04 PG16

Subang Jaya, Selangor.

Pasir Gudang, Johor.

1/7/93 1/9/00

31/8/00 1/9/01

750 850

C040 C093

Karim Fendi Kasim Selamat

HouseNo

Page 2 DREAMHOUSE LEASE Date : 28/02/2007 Client Rental Information

Client Name : Ahmad Client Number : CR56

HouseAddressHouseAddress

RentStartRentStart

RentFinishRentFinish

MonthlyRentMonthlyRent

OwnerNo

OwnerName

PG04 PG16

Skudai, Johor

Ampang, Selangor

1/7/93 1/9/00

31/8/00 1/9/01

750 850

C040 C093

Dolah

Abdullah

HouseNo

Page 1 DREAMHOUSE LEASE Date : 28/02/2007 Client Rental Information

Client Name : Rannia Client Number : CR76

Figure 2 : Collection of Dream Home leases (rent) form

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UNF to 1NF

Key attribute: clientNoRepeating group in the unnormalized table as the property rented details, which repeat for each client:Repeating Group: ( houseNo, houseAdd, rentStart, rentFinish, rent, ownerNo, oName)

clientNo

CR76

CR56

cName houseNo

houseAdd

rentStart

rentFinish

rent ownerNo

oName

Rannia PG04

PG16

Skudai, Johor.

Ampang,Selangor

1/7/93

1/9/00

31/8/00

1/9/01

750

850

C040

C093

Dolah

Abdullah

Ahmad PG04 PG 36

PG 16

Skudai, Johor.

Kuantan, Pahang.

Ampang, Selangor.

20/3/90 21/6/93

25/1/00

19/6/93 3/1/00

30/8/00

750 1000

850

C040 C093

C093

Dolah

Abdullah

Abdullah

Figure 3 : ClientRental UNF

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UNF to 1NF

As a consequences, there are multiple value at the intersection of certain rows and columns.

For examples, there are two value for houseNo (PG4 and PG16) for the client Rannia.

To transform an unnormalized table into 1NF, we ensure that there is a single value at the intersection of each row and column. This is achieved by removing the repeating group.

With this approach, remove the repeating group (house rented details) by entering the appropriate client data into each row.

The resulting First Normalize Form (1NF) ClientRental relation is shown in Figure 4.

Key attribute: clientNoRepeating group in the unnormalized table as theproperty rented details, which repeat for each client:Repeating Group: (houseNo, houseAdd, rentStart, rentFinish, rent, ownerNo, oName)

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UNF to 1NF

clientNo

CR76

CR76

CR56

CR56

CR56

cNamehouseNo

houseAdd

rentStart

rentFinish

rent ownerNo

oName

Rannia

Rannia

PG04

PG16

Skudai, Johor.

Ampang,Selangor

1/7/93

1/9/00

31/8/00

1/9/01

750

850

C040

C093

Dolah

Abdullah

Ahmad

Ahmad

Ahmad

PG04 PG 36

PG 16

Skudai, Johor.

Kuantan, Pahang.

Ampang, Selangor.

20/3/90 21/6/93

25/1/00

19/6/93 3/1/00

30/8/00

750 1000

850

C040 C093

C093

Dolah

Abdullah

Abdullah

Figure 4 : 1NF ClientRental relation

ClientRental (clientNo, houseNo, cName, houseAdd, rentStart, rentFinish, rent, ownerNo, oName)

Primary Key for the ClientRent relation is a composite key that are clientNo and houseNo

ClientRent relation is in 1NF as there is a single value at the intersection of each row and columns.

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UNF to 1NF

Relationship in Figure 4 contains data that describes client, house for rent and owner of the house, which is repeated for several times.

As a consequences, the ClientRental relation contains significant data redundancy.

If implemented, the 1NF relation would be subject to the update anomalies.

To remove some of these, transform 1NF 2NF

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Borrow(bID, bDATE,mID,mNAME,mADD,ISBN,title,rDATE)

Functional dependencies:bID, ISBN bDATE (PK)bID mID,mNAME,mADD,rDATE

(PD)ISBN title (PD)mID mNAME,mADD

(TD)

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INSURANCE(cNO,cNAME,cADD,pNO,pTYPE,

pDATE,purchaseDATE,pPRICE,aNO,aNAME,aTEL)

Functional Dependencies:cNO,pNO,aNO purcahseDATE (PK)cNO cNAME,cADD (PD)pNO pTYPE,pDATE,pPRICE (PD)aNO aNAME,aTEL (PD)

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RECEIPT(rNO,date,tNO,sID,sNAME,iNO,mNO,mDES,qty,price,amt,total,pay,balance)

Functional Dependencies:

rNO,mNO qty, iNO, amt (PK)

rNO date,tNO,sID,sNAME,total,pay,balance (PD)

mNO mDES,price (PD)

sID sNAME (TD)

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Second Normal Form (2NF)

Based on the concept of partial dependency. Dependencies based on only a part of composite primary key

2NF applies to relations with composite keys, that is, relations with PK composed of two or more attributes.

A relation with a single-attribute PK is automatically in at least 2NF.

Second Normal Form = A relation that is in 1NF and every non-PK 2NF attribute is fully functionally depends on the PK.

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CONTINUE TO NEXT PRESENTATION

TRANSFORMING UNF TO 2NF

Documents

NORMALIZATION Part 1: The Concept 1. Objectives 2 How to undertake the normalization process. How normalization uses functional dependencies to group