Normalization in DBMS

Normalization in DBMS:
1NF, 2NF, 3NF and BCNF
Hitesh Mohapatra

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
101 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
104 Lester Bangalore 9990000123
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.

The 1NF form:
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

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”.

The 2NF Form
We can break it in two tables like this:
eacher_id teacher_age
111 38
222 38
333 40
teacher_details table:
teacher_id subject
111 Maths
111 Physics
222 Biology
333 Physics
333 Chemistry
teacher_subject table:
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_id emp_name emp_zip emp_state emp_city emp_district
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.

The 3NF Form
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_id emp_nationality emp_dept dept_type dept_no_of_emp
1001 Austrian Production and planning D001 200
1001 Austrian stores D001 250
1002 American design and technical support D134 100
1002 American Purchasing department D134 600
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.

The BCNF Form
emp_nationality table:
emp_id emp_nationality
1001 Austrian
1002 American
emp_dept table:
emp_dept dept_type dept_no_of_emp
Production and planning D001 200
stores D001 250
design and technical support D134 100
Purchasing department D134 600
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.

Normalization in DBMS

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