What is Normalisation (or Normalization)? [closed]

Answer 1

Normalization is basically to design a database schema such that duplicate and redundant data is avoided. If some piece of data is duplicated several places in the database, there is the risk that it is updated in one place but not the other, leading to data corruption.

There is a number of normalization levels from 1. normal form through 5. normal form. Each normal form describes how to get rid of some specific problem, usually related to redundancy.

Some typical normalization errors:

(1) Having more than one value in a cell. Example:

UserId | Car
---------------------
1      | Toyota
2      | Ford,Cadillac

Here the "Car" column (which is a string) have several values. That offends the first normal form, which says that each cell should have only one value. We can normalize this problem away by have a separate row per car:

UserId | Car
---------------------
1      | Toyota
2      | Ford
2      | Cadillac

The problem with having several values in one cell is that it is tricky to update, tricky to query against, and you cannot apply indexes, constraints and so on.

(2) Having redundant non-key data (ie. data repeated unnecessarily in several rows). Example:

UserId | UserName | Car
-----------------------
1      | John     | Toyota
2      | Sue      | Ford
2      | Sue      | Cadillac

This design is a problem because the name is repeated per each column, even though the name is always determined by the UserId. This makes it theoretically possible to change the name of Sue in one row and not the other, which is data corruption. The problem is solved by splitting the table in two, and creating a primary key/foreign key relationship:

UserId(FK) | Car               UserId(PK) | UserName
---------------------          -----------------
1          | Toyota            1          | John
2          | Ford              2          | Sue
2          | Cadillac

Now it may seem like we still have redundant data because the UserId's are repeated; However the PK/FK constraint ensures that the values cannot be updated independently, so integrity is safe.

Is it important? Yes, it is very important. By having a database with normalization errors, you open the risk of getting invalid or corrupt data into the database. Since data "lives forever" it is very hard to get rid of corrupt data when first it has entered the database.

Don't be scared of normalization. The official technical definitions of the normalization levels are quite obtuse. It makes it sound like normalization is a complicated mathematical process. However, normalization is basically just the common sense, and you will find that if you design a database schema using common sense it will typically be fully normalized.

There are a number of misconceptions around normalization:

• some believe that normalized databases are slower, and the denormalization improves performance. This is only true in very special cases however. Typically a normalized database is also the fastest.

• sometimes normalization is described as a gradual design process and you have to decide "when to stop". But actually the normalization levels just describe different specific problems. The problem solved by normal forms above 3rd NF are pretty rare problems in the first place, so chances are that your schema is already in 5NF.

Does it apply to anything outside of databases? Not directly, no. The principles of normalization is quite specific for relational databases. However the general underlying theme - that you shouldn't have duplicate data if the different instances can get out of sync - can be applied broadly. This is basically the DRY principle.

Answer 2

It helps prevent duplicate (and worse, conflicting) data.

Can have negative impact on performance though.

Answer 3

The rules of normalisation (source: unknown)

• The key (1NF)
• The whole key (2NF)
• and nothing but the key (3NF)

... So help me Codd.

Answer 4

What is Normalization?

Normalization is a step wise formal process that allows us to decompose database tables in such a way that both data redundancy and update anomalies are minimized.

Normalization Process
Courtesy

First normal form if and only if the domain of each attribute contains only atomic values (an atomic value is a value that cannot be divided), and the value of each attribute contains only a single value from that domain(example:- domain for the gender column is: "M", "F". ).

First normal form enforces these criteria:

• Eliminate repeating groups in individual tables.
• Create a separate table for each set of related data.
• Identify each set of related data with a primary key

Second normal form = 1NF + no partial dependencies i.e. All non-key attributes are fully functional dependent on the primary key.

Third normal form = 2NF + no transitive dependencies i.e. All non-key attributes are fully functional dependent DIRECTLY only on the primary key.

Boyce–Codd normal form (or BCNF or 3.5NF) is a slightly stronger version of the third normal form (3NF).

Note:- Second, Third, and Boyce–Codd normal forms are concerned with functional dependencies. Examples

Fourth normal form = 3NF + remove Multivalued dependencies

Fifth normal form = 4NF + remove join dependencies

Answer 5

It is intended to reduce redundancy of data.

For a more formal discussion, see the Wikipedia http://en.wikipedia.org/wiki/Database_normalization

I'll give a somewhat simplistic example.

Assume an organization's database that usually contains family members

id, name, address
214 Mr. Chris  123 Main St.
317 Mrs. Chris 123 Main St.

could be normalized as

id name familyID
214 Mr. Chris 27
317 Mrs. Chris 27

and a family table

ID, address
27 123 Main St.

Near-Complete normalization (BCNF) is usually not used in production, but is an intermediate step. Once you've put the database in BCNF, the next step is usually to De-normalize it in a logical way to speed up queries and reduce the complexity of certain common inserts. However, you can't do this well without properly normalizing it first.

The idea being that the redundant information is reduced to a single entry. This is particularly useful in fields like addresses, where Mr. Chris submits his address as Unit-7 123 Main St. and Mrs. Chris lists Suite-7 123 Main Street, which would show up in the original table as two distinct addresses.

Typically, the technique used is to find repeated elements, and isolate those fields into another table with unique ids and to replace the repeated elements with a primary key referencing the new table.