What is normalization? What is the advantage of normalization?

The process of separating data into distinct, unique sets is called normalization. This is implemented to imorove the performance of the RDBMS, such as reduceces redunbdancy of data and data inconsistency.

Normalization is the process of removing redundant data from your tables in order to improve storage efficiency, data integrity and scalability

Database normalization is a series of steps followed to obtain a database design that allows for consistent storage and efficient access of data in a relational database .These steps reduce data redundancy and the risk of data becoming inconsistent

Normalization is the process used to reduce the unnecessary repetetion of data i.e, redundant data.It is performed on the data which is redundant and makes the data in a normalized format.It is of step-by-step processIstNotmal FormIIndNormal formIIIrdNormalformIVth Normalform or BoyceCodd Normal formBy perofmring this we will get the data in the Normalized formati.,e from DBMS to RDBMS.

what is the advantage of normalization (briefly)

Normalization solely reduces redundancy  and it give rises to a database which consists of distinct yet related tables.

  This results in database consistency, flexible data accesses .

Normalization is the process of organizing data in a database. This includes creating tables and establishing relationships between those tables according to rules designed both to protect the data and to make the database more flexible by eliminating two factors: redundancy and inconsistent dependency.
Redundant data wastes disk space and creates maintenance problems. If data that exists in more than one place must be changed, the data must be changed in exactly the same way in all locations. A customer address change is much easier to implement if that data is stored only in the Customers table and nowhere else in the database.
What is an "inconsistent dependency"? While it is intuitive for a user to look in the Customers table for the address of a particular customer, it may not make sense to look there for the salary of the employee who calls on that customer. The employee's salary is related to, or dependent on, the employee and thus should be moved to the Employees table. Inconsistent dependencies can make data difficult to access; the path to find the data may be missing or broken.
There are a few rules for database normalization. Each rule is called a "normal form." If the first rule is observed, the database is said to be in "first normal form." If the first three rules are observed, the database is considered to be in "third normal form." Although other levels of normalization are possible, third normal form is considered the highest level necessary for most applications.
As with many formal rules and specifications, real world scenarios do not always allow for perfect compliance. In general, normalization requires additional tables and some customers find this cumbersome. If you decide to violate one of the first three rules of normalization, make sure that your application anticipates any problems that could occur, such as redundant data and inconsistent dependencies.

NOTE: The following descriptions include examples.

First Normal Form

• 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.

Do not use multiple fields in a single table to store similar data. For example, to track an inventory item that may come from two possible sources, an inventory record may contain fields for Vendor Code 1 and Vendor Code 2.
But what happens when you add a third vendor? Adding a field is not the answer; it requires program and table modifications and does not smoothly accommodate a dynamic number of vendors. Instead, place all vendor information in a separate table called Vendors, then link inventory to vendors with an item number key, or vendors to inventory with a vendor code key.

Second Normal Form

• Create separate tables for sets of values that apply to multiple records.
• Relate these tables with a foreign key.

Records should not depend on anything other than a table's primary key (a compound key, if necessary). For example, consider a customer's address in an accounting system. The address is needed by the Customers table, but also by the Orders, Shipping, Invoices, Accounts Receivable, and Collections tables. Instead of storing the customer's address as a separate entry in each of these tables, store it in one place, either in the Customers table or in a separate Addresses table.

Third Normal Form

• Eliminate fields that do not depend on the key.

Values in a record that are not part of that record's key do not belong in the table. In general, any time the contents of a group of fields may apply to more than a single record in the table, consider placing those fields in a separate table.
For example, in an Employee Recruitment table, a candidate's university name and address may be included. But you need a complete list of universities for group mailings. If university information is stored in the Candidates table, there is no way to list universities with no current candidates. Create a separate Universities table and link it to the Candidates table with a university code key.
EXCEPTION: Adhering to the third normal form, while theoretically desirable, is not always practical. If you have a Customers table and you want to eliminate all possible interfield dependencies, you must create separate tables for cities, ZIP codes, sales representatives, customer classes, and any other factor that may be duplicated in multiple records. In theory, normalization is worth pursuing; however, many small tables may degrade performance or exceed open file and memory capacities.
It may be more feasible to apply third normal form only to data that changes frequently. If some dependent fields remain, design your application to require the user to verify all related fields when any one is changed.

Other Normalization Forms

Fourth normal form, also called Boyce Codd Normal Form (BCNF), and fifth normal form do exist, but are rarely considered in practical design. Disregarding these rules may result in less than perfect database design, but should not affect functionality.

               **********************************                 Examples of Normalized Tables               ********************************** Normalization Examples: Unnormalized table:    Student#   Advisor   Adv-Room  Class1   Class2   Class3    -------------------------------------------------------    1022       Jones      412      101-07   143-01   159-02    4123       Smith      216      201-01   211-02   214-01

1. First Normal Form: NO REPEATING GROUPS
   Tables should have only two dimensions. Since one student has several classes, these classes should be listed in a separate table. Fields Class1, Class2, & Class3 in the above record are indications of design trouble.
   Spreadsheets often use the third dimension, but tables should not. Another way to look at this problem: with a one-to-many relationship, do not put the one side and the many side in the same table. Instead, create another table in first normal form by eliminating the repeating group (Class#), as shown below:

          Student#   Advisor   Adv-Room    Class#       ---------------------------------------       1022      Jones      412       101-07       1022      Jones      412       143-01       1022      Jones      412       159-02       4123      Smith      216       201-01       4123      Smith      216       211-02       4123      Smith      216       214-01

2. Second Normal Form: ELIMINATE REDUNDANT DATA
   Note the multiple Class# values for each Student# value in the above table. Class# is not functionally dependent on Student# (primary key), so this relationship is not in second normal form.
   The following two tables demonstrate second normal form:

       Students:   Student#    Advisor   Adv-Room                ------------------------------                1022        Jones       412                4123        Smith       216    Registration:   Student#    Class#                    ------------------                    1022        101-07                    1022        143-01                    1022        159-02                    4123        201-01                    4123        211-02                    4123        214-01

3. Third Normal Form: ELIMINATE DATA NOT DEPENDENT ON KEY
   In the last example, Adv-Room (the advisor's office number) is functionally dependent on the Advisor attribute. The solution is to move that attribute from the Students table to the Faculty table, as shown below:

       Students:   Student#    Advisor                -------------------                1022        Jones                4123        Smith    Faculty:    Name    Room    Dept                --------------------                Jones   412     42                Smith   216     42

send me advantages of nomalization.

The main advantage of normalisation is that it helps to reduce redundancy.

However too much of normalisation is also not preferred as it creates too many tables leading too more nos fo joins making the query even more complex.Normalisation upto 3NF is generally preferred.

what is normalization? what is the advantage of normalisation

what are te problems that may arise if a system is created without completing normalisation first

The answer for this normalization is good. If u don't mine can u give me one more example for normalization.

The Process of Simplifying the structure of data. Normalization increase granularity and Granularity is the scope of a definition for any particular thing.The more granular a data model is the easier it becomes to manage ,up to a point ,depending ,of course, on the application of the database model.

Normalization is a process of reviewing a data model to remove data redundency, maintain data intergrity, and make the data model as simple as possible. There are 3 normalization forms that are generally used, and an additional fourth and fifth normal form

The advantages of normalization is to remove data redundency