Normal Forms in DBMS | Types of Normal Forms with Examples Code Answer

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Forms of normalization are given underneath:

  1. First Normal Form (1NF)
  2. Second Normal Form (2NF)
  3. Third Normal Form (3NF)
  4. Boyce-codd Normal Form (BCNF)
  5. Fourth Normal Form (4NF)
  6. Fifth Normal Form (5NF)

First Normal Form (1NF):

“A connection pattern R is in 1NF, on the off chance that it doesn’t have any composite attributes, multivalued attribute or their mix.”

The target of first normal structure is that the table ought to contain no rehashing gatherings of data. Data is partitioned into coherent units called elements or tables

All credits (segment) in the element (table) should be single esteemed.

Rehashing or multi esteemed credits are moved into a different element (table) and a relationship is set up between the two tables or substances.

Illustration of the first normal structure:

Consider the accompanying Customer table.

cid name address contact_no
society city
C01 aaa Anmol Aasir,Ajmer {1234567988}
C02 bbb near mohan park,delhi {123,333,4445}
C03 ccc gandhi park , surramya

Here, address is a composite quality, which is additionally partitioned into two segment society and city. And characteristic contact_no is multivalued property.

Issues with this connection are –

It is absurd to expect to store numerous qualities in a solitary field in a connection. thus, if any client has more than one contact number, it is preposterous to expect to store those numbers.

Another issue is identified with data recovery. Assume, here, if there is a need to discover all clients having a place with some specific city, it is hard to recover. The explanation is: city name for all clients is joined with society names and put away entire as a location.

Answer for composite quality

Supplement separate ascribes in a connection for each sub-trait of a composite characteristic.

In our model, embed two separate credits for Society and city in a connection instead of single composite ascribes address. Presently, embed information esteems independently for Society and City for all tuples.


cid name Society
city contact_no
C01 aaa Anmol Aasir Ajmer {1234567988}
C02 bbb near mohan park delhi {123,333,4445}
C03 ccc gandhi park surramya

Answer for Multi-esteemed characteristic

Two methodologies are accessible to tackle issue of multi-esteemed quality

1. First Approach:

In a First methodology, decide greatest reasonable qualities for a multi-esteemed attribute. In our case, if most extreme two numbers are permitted to store, embed two separate credits ascribes to store contact numbers as appeared.


cid name Society city
contact_no1 contact_no2 contact_no3
C01 aaa Anmol Aasir Ajmer 1234567988
C02 bbb near mohan park delhi 123 333 4445
C03 ccc gandhi park surramya

Now, if client has just one contact number or no contact number, at that point keep the connected field void for tuple of that client. If client has two contact numbers, store number in related fields. If client has more than two contact numbers, store two numbers and disregard any remaining numbers.

2.Second Approach:

In a second methodology, eliminate the multi-esteemed property that disregards 1NF and place it in a different connection alongside the essential key of given unique connection. The essential key of new connection is the mix of multi-esteemed property and essential key of old connection. for instance, for our situation, eliminate the contact_no trait and spot it with cid in a different connection customer_contact. Essential Key for connection Customer_contact will be mix of cid and contact_no.


cid name Society city
C01 aaa Anmol Aasir Ajmer
C02 bbb near mohan park delhi
C03 ccc gandhi park surramya


cid contact_no
C01 1234567988
C02 123
C02 333
C02 4445

First methodology is simple. But it is not generally conceivable to put limitation on most extreme permissible values. It likewise presents invalid qualities for many fields.

Second methodology is prevalent as it does not experience the ill effects of downsides of first methodology. Yet, it is somewhat confounded one. For model, to show all data about any/all clients, two relations – Customer and Customer contact – should be gotten to.


“A connection mapping R is in 2NF, in the event that It is in First Normal Form, and each non-prime trait of connection is completely practically subject to essential key.”

A connection can abuse 2NF just when it has more than one trait in mix as an essential key. if connection has just single trait as an essential key, at that point, connection will be in 2NF.


consider the following connection Table Depositor_Account


This connection contains following utilitarian conditions.

FD1: {Cid, ano} – > {access_date, balance, bname}

FD2: ano – > {balance, bname}

In this connection diagram, access_date, equilibrium and bname are non – prime ascribes. Among all these three ascribes, access_date is completely subject to essential key (cid and ano). Be that as it may, equilibrium and bname are not completely subject to essential key. tey rely upon ano as it were.

Along these lines, this connection is not in Second normal structure. Such sort of partial conditions brings about information excess.


Break down the relation with the end goal that, resultant relations do not have any incomplete useful reliance. For this reason, eliminate the fractional ward non-prime ascribes that disregards 2NF in connection. Spot them in a different new connection alongside the great characteristic on which they completely depend.

In our model, equilibrium and bname are fractional dependent characteristic on essential key. along these lines, eliminate them and spot in isolated relation called account along with prime characteristic ano. For connection Account, ano will be a Primary key.

The Depositor_ account connection will be decomposed in two separate relations, called Account_holder and Account.



“A connection diagram R is in 3NF, on the off chance that it is in Second normal structure, and no non-prime characteristic of connection is transitively subject to essential key.”

Third normal structure guarantees that the connection does not have any non-prime trait transitively subject to essential key. At the end of the day, it guarantees that all the non-prime ascribes of connection straightforwardly rely upon the essential key.


Consider the accompanying connection pattern Account_Branch


This relation contains following useful conditions.

FD1: ano – > {balance, bname, baddress}, and

FD2: bname – > baddress

In this connection mapping, there is a useful reliance ano – > bname between ano and bname as appeared in FD1. additionally, there is another useful reliance bname – > baddress between bname and baddress as appeared in FD2. moreover, bname is a non-prime quality. In this way, there is a transitive reliance from ano to baddress, indicated by ano – > baddress.

Such sort of transitive conditions brings about information excess. In this connection, branch address will be put away consistently for each record of a similar branch, involving more measure of memory.


Deteriorate the connection so that, resultant relations do not have any non-prime property transitively subject to essential key. For this reason, eliminate the transitively dependent non-prime ascribes that abuses 3NF from connection. Spot them in a different new connection alongside the non-prime trait because of which transitive reliance occurred. The essential key of new connection will be the non-prime attribute.

In our model, baddress is transitively reliant on ano because of non-prime characteristic bname. In this way, eliminate baddress and place it in isolated connection called Branch alongside the non-prime property bname. for connection Branch, bname will be an essential key.

The Account_Branch connection will be decayed in two separate relations called Account and Branch.


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