NORMALIZATION

What is Database NORMALIZATION? What are different techniques to normalize DB Tables?

Database Normalization is a technique of organizing the data in the database. Normalization is a systematic approach of decomposing tables to eliminate data redundancy and undesirable characteristics like Insertion, Update and Deletion Anomalies. It is a multi-step process that puts data into tabular form by removing duplicated data from the relation tables.

Normalization is used for mainly two purpose,

·       Eliminating redundant(useless) data.

·       Ensuring data dependencies make sense i.e. data is logically stored.

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Problem Without Normalization

Without Normalization, it becomes difficult to handle and update the database, without facing data loss. Insertion, Updation and Deletion anomalies are very frequent if Database is not Normalized. To understand these anomalies let us take an example of Student table.

S_id	S_Name	S_Address	Subject_opted
401	Adam	Noida	Bio
402	Alex	Panipat	Maths
403	Stuart	Jammu	Maths
404	Adam	Noida	Physics

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·       Updation Anamoly : To update address of a student who occurs twice or more than twice in a table, we will have to update S_Address column in all the rows, else data will become inconsistent.

·       Insertion Anamoly : Suppose for a new admission, we have a Student id(S_id), name and address of a student but if student has not opted for any subjects yet then we have to insert NULL there, leading to Insertion Anamoly.

·       Deletion Anamoly : If (S_id) 401 has only one subject and temporarily he drops it, when we delete that row, entire student record will be deleted along with it.

Let’s understand each of them with the help of below Example:
Consider the below Table:

EMPLOYEE_DEPARTMENT with Attributes:

EMPNO(PK)

NAME

DEPTNO

DEPT_LOC

DEPT_MANAGER

Table is having some records with Entries to each of the column.

Insertion Anomaly:

Whenever we will insert new Employee will have to assign it to some Department as well which

will work fine. Now suppose you want to introduce New Department and will think about

Employee Assignment later.

So, in above case as EMPNO is defined as Primary Key- will not allow you to insert any record

without Employee initiation which leads to Insert Anomaly and further needs Normalization.

So, if we have Normalized Tables then we can insert Department Details in separate table and

later can assign Employees to that department whenever there is requirement.

EMPLOYEE(EMPNO,NAME,DEPTNO) DEPARTMENT(DEPTNO,DEPT_LOC, DEPT_MANAGER)

Delete Anomaly:

Consider there are some Employees in one Department and all have resigned So, on their last

day Details needs to be deleted from the table. But Department detail will also be removed from

your Table which leads to Deletion Anomaly where deletion of some data lead to loss of other

information which might require in future.

So, if we have Normalized Tables we can actually Delete Employee details separately from

Employee Table but your Department Details will still be available in Department Table.

EMPLOYEE(EMPNO,NAME,DEPTNO) DEPARTMENT(DEPTNO,DEPT_LOC, DEPT_MANAGER)

Update Anomaly:

Suppose Manager of a Department has changed. This requires updation of multiple entries

against that Department number. If any case we will fail to update some of the records then we

will have two managers for the same department and one is not available which leads to

inconsistency in the DB(Update Anomaly).

So, if we have Normalized Tables then we can actually update Department Manager in one table.

EMPLOYEE(EMPNO,NAME,DEPTNO) DEPARTMENT(DEPTNO,DEPT_LOC, DEPT_MANAGER)

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Normalization Rule

Normalization rule are divided into following normal form.

1.        First Normal Form

2.       Second Normal Form

3.       Third Normal Form

4.       BCNF

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First Normal Form (1NF)

As per First Normal Form, no two Rows of data must contain repeating group of information i.e each set of column must have a unique value, such that multiple columns cannot be used to fetch the same row. Each table should be organized into rows, and each row should have a primary key that distinguishes it as unique.

The Primary key is usually a single column, but sometimes more than one column can be combined to create a single primary key. For example consider a table which is not in First normal form

Student Table :

Student	Age	Subject
Adam	15	Biology, Maths
Alex	14	Maths
Stuart	17	Maths

In First Normal Form, any row must not have a column in which more than one value is saved, like separated with commas. Rather than that, we must separate such data into multiple rows.

Student Table following 1NF will be :

Student	Age	Subject
Adam	15	Biology
Adam	15	Maths
Alex	14	Maths
Stuart	17	Maths

Using the First Normal Form, data redundancy increases, as there will be many columns with same data in multiple rows but each row as a whole will be unique.

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Second Normal Form (2NF)

As per the Second Normal Form there must not be any partial dependency of any column on primary key. It means that for a table that has concatenated primary key, each column in the table that is not part of the primary key must depend upon the entire concatenated key for its existence. If any column depends only on one part of the concatenated key, then the table fails Second normal form.

In example of First Normal Form there are two rows for Adam, to include multiple subjects that he has opted for. While this is searchable, and follows First normal form, it is an inefficient use of space. Also in the above Table in First Normal Form, while the candidate key is {Student, Subject}, Age of Student only depends on Student column, which is incorrect as per Second Normal Form. To achieve second normal form, it would be helpful to split out the subjects into an independent table, and match them up using the student names as foreign keys.

New Student Table following 2NF will be :

Student	Age
Adam	15
Alex	14
Stuart	17

In Student Table the candidate key will be Student column, because all other column i.e Age is dependent on it.

New Subject Table introduced for 2NF will be :

Student	Subject
Adam	Biology
Adam	Maths
Alex	Maths
Stuart	Maths

In Subject Table the candidate key will be {Student, Subject} column. Now, both the above tables qualifies for Second Normal Form and will never suffer from Update Anomalies. Although there are a few complex cases in which table in Second Normal Form suffers Update Anomalies, and to handle those scenarios Third Normal Form is there.

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Third Normal Form (3NF)

Third Normal form applies that every non-prime attribute of table must be dependent on primary key, or we can say that, there should not be the case that a non-prime attribute is determined by another non-prime attribute. So this transitive functional dependency should be removed from the table and also the table must be in Second Normal form. For example, consider a table with following fields.

Student_Detail Table :

Student_id

Student_name

DOB

Street

city

State

Zip

In this table Student_id is Primary key, but street, city and state depends upon Zip. The dependency between zip and other fields is called transitive dependency. Hence to apply 3NF, we need to move the street, city and state to new table, with Zip as primary key.

New Student_Detail Table :

Student_id

Student_name

DOB

Zip

Address Table :

Zip

Street

city

state

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The advantage of removing transtive dependency is,

·       Amount of data duplication is reduced.

·       Data integrity achieved.

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Boyce and Codd Normal Form (BCNF)

Boyce and Codd Normal Form is a higher version of the Third Normal form. This form deals with certain type of anamoly that is not handled by 3NF. A 3NF table which does not have multiple overlapping candidate keys is said to be in BCNF. For a table to be in BCNF, following conditions must be satisfied:

·       R must be in 3rd Normal Form

·       and, for each functional dependency ( X -> Y ), X should be a super Key.

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