1.81M
Category: databasedatabase

Database normalization. Module 9

1.

Database
normalization
• Module 9

2.

Agenda
• What is normalization?
• First normal form
• Second normal form
• Third normal form
• Denormalization
2

3.

What is normalization?
The process of organizing the columns and
tables of a relational database to minimize
data redundancy
“Abnormal” DB
(unnormalized form ,
UNF)
normalization
“Normal” DB
(normalized form, NF)
3

4.

Data redundancy
The existence of data that is an additional
copy of the actual data or a small part of
them. Data redundancy leads to the
modification anomalies.
ID
FIRSTNAME
1 Яськів
2 Мельник
3 Коваленко
4 Олійник
LASTNAME
Антон
Ольга
Тарас
Василь
POSITION
Boss
Manager
Manager
Manager
DATE_EMPLOYMENT ID_DEPARTMENT
10/11/1998
03/09/2011
04/15/2008
11/25/2010
ID_BOSS
1
1
2
3
RATE BONUS
8600
1
5400
1
4800
1
6000
NAME
Sun
Sun
Moon
Saturn
CITY
Lviv
Lviv
Kyiv
Lviv
4

5.

Modification anomalies
• Insert anomalies
• Update anomalies
• Delete anomalies
5

6.

Goals of the normalization
• Free the DB of modification anomalies
• Minimize redesign when extending the DB
structure
• Make the DB more informative
• Make the DB suitable for querying
6

7.

Normal forms
• First normal form (1NF)
• Second normal form (2NF)
• Third normal form (3NF)
• Other normal forms
Normal form of a DB is a set of rules which
the DB has to meet for decreasing the data
redundancy.
7

8.

First normal form (1NF)
• No duplicate rows – row uniqueness
• No repeating groups of columns – column
uniqueness
• Every row-and-column intersection
contains exactly one value from the
applicable domain – data atomicity
8

9.

Row uniqueness
• Duplicates of rows should be eliminated
• In case when we really need the same
values in different rows, we can use an
additional field and nominate it as a
primary key
ID_EMPLOYEE VISIT_DATE
ROOM_NAME
1
10/20/2015
215
2
10/21/2015
309
1
10/21/2015
302
2
10/21/2015
309
ID
ID_EMPLOYEE
1
2
3
4
1
2
1
2
VISIT_DATE
ROOM_NAME
10/20/2015
215
10/21/2015
309
10/21/2015
302
10/21/2015
309
9

10.

Column uniqueness
• Repeating groups of columns should be
eliminated
ID_EMPLOYEE VISIT_DATE ROOM_NAME1 ROOM_NAME2 ROOM_NAME3
1 10/20/2015
215
2 10/21/2015
309
507
215
1 10/21/2015
302
ID
ID_EMPLOYEE
1
2
3
5
6
VISIT_DATE
ROOM_NAME
1
10/20/2015
215
2
10/21/2015
309
1
10/21/2015
302
2
10/21/2015
507
2
10/21/2015
215
10

11.

Data atomicity
• There is a single value in each field of each
row.
• This value is from selected domain
• NULL values could be also allowed
ID_EMPLOYEE VISIT_DATE
ROOM_NAME
1
10/20/2015
215
2
10/21/2015 309, 507, 215
1
10/21/2015
302
ID
ID_EMPLOYEE
1
2
3
5
6
1
2
1
2
2
VISIT_DATE
ROOM_NAME
10/20/2015
215
10/21/2015
309
10/21/2015
302
10/21/2015
507
10/21/2015
215
11

12.

UNF->1NF
• Eliminate duplicative columns from the
same table.
• Create separate tables for each group of
related data and identify each row with a
unique column or set of columns (the
primary key).
12

13.

Functional dependency
• Describes relationship between columns in
a table.
• If A and B are columns of the table R, B is
functionally dependent on A (denoted
A→B), if each value of A in R is associated
with exactly one value of B in R.
ID→LASTNAME
ID→FIRSTNAME
LASTNAME → FIRSTNAME
13

14.

Second normal form (2NF)
• 1NF
• No partial functional dependencies
ID FIRSTNAME LASTNAME POSITION ID_DEPARTMENT ID_BOSS RATE BONUS NAME CITY PROJECT_ID PROJECT_NAME
1 Яськів
Антон
Boss
1
8600
Sun
Lviv
1 Delta
2 Мельник
Ольга
Manager
1
1 5400
Sun
Lviv
1 Delta
3 Коваленко Тарас
Manager
2
1 4800
Moon Kyiv
2 Alpha
3 Коваленко Тарас
Manager
2
1 4800
Moon Kyiv
3 Omega
4 Олійник
Василь
Manager
3
1 6000
Saturn Lviv
1 Delta
ID FIRSTNAME LASTNAME POSITION ID_DEPARTMENT ID_BOSS RATE BONUS NAME CITY
1 Яськів
Антон
Boss
1
8600
Sun
Lviv
2 Мельник
Ольга
Manager
1
1 5400
Sun
Lviv
3 Коваленко Тарас
Manager
2
1 4800
Moon Kyiv
4 Олійник
Василь
Manager
3
1 6000
Saturn Lviv
ID
PROJECT_ID
1
1
2
1
3
2
3
3
4
1
PROJECT_ID PROJECT_NAME
1 Delta
2 Alpha
3 Omega
14

15.

1NF->2NF
• Identify functional dependencies in the
table.
• If partial dependencies exist on the primary
key remove them by placing them in a new
table along with copy of their determinant.
15

16.

Third normal form (3NF)
• 2NF
• No transitive dependencies, i.e. no non-key
field depends upon another.
ID FIRSTNAME LASTNAME POSITION ID_DEPARTMENT ID_BOSS RATE BONUS NAME CITY
1 Яськів
Антон
Boss
1
8600
Sun
Lviv
2 Мельник
Ольга
Manager
1
1 5400
Sun
Lviv
3 Коваленко Тарас
Manager
2
1 4800
Moon Kyiv
4 Олійник
Василь
Manager
3
1 6000
Saturn Lviv
ID FIRSTNAME LASTNAME POSITION ID_BOSS RATE BONUS ID_DEPARTMENT
1 Яськів
Антон
Boss
8600
1
2 Мельник Ольга
Manager
1 5400
1
3 Коваленко Тарас
Manager
1 4800
2
4 Олійник
Василь
Manager
1 6000
3
ID_DEPARTMENT NAME CITY
1 Sun
Lviv
2 Moon Kyiv
3 Saturn Lviv
16

17.

2NF->3NF
• Identify functional dependencies in the
table.
• If transitive dependencies exist on the
primary key remove them by placing them
in a new table along with copy of their
determinant.
17

18.

Normalization: question
How does a normalization affect the
productivity of such operations:
• Insert
• Update
• Delete
• Select
?
18

19.

Denormalization
• Denormalized databases fair well under
heavy read-load and when the application
is read intensive
• But because the data is duplicated, the
updates and inserts become complex and
costly
19

20.

More information
• http://databases.about.com/od/specificpro
ducts/a/normalization.htm
• http://holowczak.com/databasenormalization/
• http://www.essentialsql.com/get-ready-tolearn-sql-database-normalizationexplained-in-simple-english/
• http://www.studytonight.com/dbms/datab
ase-normalization.php
20

21.

Thank you!
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