Normalization
Normalization is a process of organizing the data
in database to avoid data redundancy, insertion
anomaly, update anomaly & deletion anomaly.
Let’s discuss about anomalies first then we will
discuss normal forms with examples.
Anomalies in DBMS
There are three types of anomalies that occur
when the database is not normalized. These are –
Insertion, update and deletion anomaly. Let’s
take an example to understand this.
Example: Suppose a manufacturing company
stores the employee details in a table named
employee that has four attributes: emp_id for
storing employee’s id, emp_name for storing
employee’s name, emp_address for storing
employee’s address and emp_dept for storing the
department details in which the employee works.
At some point of time the table looks like this:
emp_id emp_name emp_address emp_dept
01 Rick Delhi D001
101 Rick Delhi D002
123 Maggie Agra D890
166 Glenn Chennai D900
166 Glenn Chennai D004
The above table is not normalized. We will see
the problems that we face when a table is not
normalized.
Update anomaly: In the above table we have two
rows for employee Rick as he belongs to two
departments of the company. If we want to
update the address of Rick then we have to
update the same in two rows or the data will
become inconsistent. If somehow, the correct
address gets updated in one department but not
in other then as per the database, Rick would be
having two different addresses, which is not
correct and would lead to inconsistent data.
Insert anomaly: Suppose a new employee joins
the company, who is under training and currently
not assigned to any department then we would
not be able to insert the data into the table if
emp_dept field doesn’t allow nulls.
Delete anomaly: Suppose, if at a point of time
the company closes the department D890 then
deleting the rows that are having emp_dept as
D890 would also delete the information of
employee Maggie since she is assigned only to this
department.
To overcome these anomalies we need to
normalize the data. In the next section we will
discuss about normalization.
Normalization
Here are the most commonly used normal forms:
First normal form(1NF)
Second normal form(2NF)
Third normal form(3NF)
Boyce & Codd normal form (BCNF)
First normal form (1NF)
As per the rule of first normal form, an attribute
(column) of a table cannot hold multiple values.
It should hold only atomic values.
Example: Suppose a company wants to store the
names and contact details of its employees. It
creates a table that looks like this:
emp_id emp_name emp_address emp_mobile
101 Herschel New Delhi 8912312390
102 Jon Kanpur 8812121212
9900012222
103 Ron Chennai 7778881212
9990000123
104 Lester Bangalore
8123450987
Two employees (Jon & Lester) are having two
mobile numbers so the company stored them in
the same field as you can see in the table above.
This table is not in 1NF as the rule says “each
attribute of a table must have atomic (single)
values”, the emp_mobile values for employees
Jon & Lester violates that rule.
To make the table complies with 1NF we should
have the data like this:
emp_id emp_name emp_address emp_mobile
101 Herschel New Delhi 8912312390
102 Jon Kanpur 8812121212
102 Jon Kanpur 9900012222
103 Ron Chennai 7778881212
104 Lester Bangalore 9990000123
104 Lester Bangalore 8123450987
Second normal form (2NF)
A table is said to be in 2NF if both the following
conditions hold:
Table is in 1NF (First normal form)
No non-prime attribute is dependent on the
proper subset of any candidate key of table.
An attribute that is not part of any candidate key
is known as non-prime attribute.
Example: Suppose a school wants to store the
data of teachers and the subjects they teach.
They create a table that looks like this: Since a
teacher can teach more than one subjects, the
table can have multiple rows for a same teacher.
teacher_id Subject teacher_age
111 Maths 38
111 Physics 38
222 Biology 38
333 Physics 40
333 Chemistry 40
Candidate Keys: {teacher_id, subject}
Non prime attribute: teacher_age
The table is in 1 NF because each attribute has
atomic values. However, it is not in 2NF because
non prime attribute teacher_age is dependent on
teacher_id alone which is a proper subset of
candidate key. This violates the rule for 2NF as
the rule says “no non-prime attribute is
dependent on the proper subset of any candidate
key of the table”.
To make the table complies with 2NF we can
break it in two tables like this:
teacher_details table:
teacher_id teacher_age
111 38
222 38
333 40
teacher_subject table:
teacher_id subject
111 Maths
111 Physics
222 Biology
333 Physics
333 Chemistry
Now the tables comply with Second normal form
(2NF).
Third Normal form (3NF)
A table design is said to be in 3NF if both the
following conditions hold:
Table must be in 2NF
Transitive functional dependency of non-
prime attribute on any super key should be
removed.
An attribute that is not part of any candidate
key is known as non-prime attribute.
In other words 3NF can be explained like this: A
table is in 3NF if it is in 2NF and for each
functional dependency X-> Y at least one of the
following conditions hold:
X is a super key of table
Y is a prime attribute of table
An attribute that is a part of one of the candidate
keys is known as prime attribute.
Example: Suppose a company wants to store the
complete address of each employee, they create
a table named employee_details that looks like
this:
emp_ emp_
emp_id emp_zip emp_city emp_district
name state
1001 John 282005 UP Agra Dayal Bagh
1002 Ajeet 222008 TN Chennai M-City
1006 Lora 282007 TN Chennai Urrapakkam
1101 Lilly 292008 UK Pauri Bhagwan
1201 Steve 222999 MP Gwalior Ratan
Super keys: {emp_id}, {emp_id, emp_name},
{emp_id, emp_name, emp_zip}…so on
Candidate Keys: {emp_id}
Non-prime attributes: all attributes except
emp_id are non-prime as they are not part of any
candidate keys.
Here, emp_state, emp_city & emp_district
dependent on emp_zip. And, emp_zip is
dependent on emp_id that makes non-prime
attributes (emp_state, emp_city & emp_district)
transitively dependent on super key (emp_id).
This violates the rule of 3NF.
To make this table complies with 3NF we have to
break the table into two tables to remove the
transitive dependency:
employee table:
emp_id emp_name emp_zip
1001 John 282005
1002 Ajeet 222008
1006 Lora 282007
1101 Lilly 292008
1201 Steve 222999
employee_zip table:
emp_zip emp_state emp_city emp_district
282005 UP Agra Dayal Bagh
222008 TN Chennai M-City
282007 TN Chennai Urrapakkam
292008 UK Pauri Bhagwan
222999 MP Gwalior Ratan
Boyce Codd normal form (BCNF)
It is an advance version of 3NF that’s why it is
also referred as 3.5NF. BCNF is stricter than 3NF.
A table complies with BCNF if it is in 3NF and for
every functional dependency X->Y, X should be
the super key of the table.
Example: Suppose there is a company wherein
employees work in more than one department.
They store the data like this:
emp emp_nati dept_ dept_no_
emp_dept
_id onality type of_emp
Production and
1001 Austrian D001 200
planning
1001 Austrian stores D001 250
design and
1002 American technical D134 100
support
Purchasing
1002 American D134 600
department
Functional dependencies in the table above:
emp_id -> emp_nationality
emp_dept -> {dept_type, dept_no_of_emp}
Candidate key: {emp_id, emp_dept}
The table is not in BCNF as neither emp_id nor
emp_dept alone are keys.
To make the table comply with BCNF we can
break the table in three tables like this:
emp_nationality table:
emp_id emp_nationality
1001 Austrian
1002 American
emp_dept table:
emp_dept dept_type dept_no_of_emp
Production and
D001 200
planning
stores D001 250
design and
D134 100
technical support
Purchasing
D134 600
department
emp_dept_mapping table:
emp_id emp_dept
1001 Production and planning
1001 stores
1002 design and technical support
1002 Purchasing department
Functional dependencies:
emp_id -> emp_nationality
emp_dept -> {dept_type, dept_no_of_emp}
Candidate keys:
For first table: emp_id
For second table: emp_dept
For third table: {emp_id, emp_dept}
This is now in BCNF as in both the functional
dependencies left side part is a key.
