Hi what is the Normalization? and the types?

Normalization is a process through which you can improve your database design so that it consumes less memory. It is the process through which you will remove the duplicate storage of same data. But it will make your queries complex. Studying normalization will not make you understand the use of it, try to apply the principles in your current design. read less

In Simple words, Normalization is to avoid the discrepancies or duplicates and maintain the data to retrieve easily. Mostly if you meet 2 or 3 Normal Forms then its enough for Database. Not required to satisfy all NF's. It may decrease the performance of DB if we try to satisfy all NF's and its not possible also. Now-e-days even doing De-Normalization in DB for some cases to achieve performance. read less

Normalization is a process of applying a set of rules on your tables in order to reduce data redundancy and eliminate Insert,Update,Delete anomolies. For e.g. you decompose table A with 10 columns into table B and table C. Out of 10 columns in table A few will be part of table B and few will be part of table C. There are 3 normal forms generally used in case of OLTP (Online Transaction Processing) databases. They are 1NF- no multi valued attributes in table, 2NF- all columns must be fully functionally dependent on PK, 3NF-no transitive dependency of any column. You can refer to this link for examples: https://en.wikipedia.org/wiki/Database_normalization read less

Normalization of Database Database Normalisation 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 Anamolies. 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 reduntant(useless) data. Ensuring data dependencies make sense i.e data is logically stored. Problem Without Normalization Without Normalization, it becomes difficult to handle and update the database, without facing data loss. Insertion, Updation and Deletion Anamolies 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 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. Normalization Rule Normalization rule are divided into following normal form. First Normal Form Second Normal Form Third Normal Form BCNF 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. 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. 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 The advantage of removing transtive dependency is, Amount of data duplication is reduced. Data integrity achieved. 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. BCNF Normal Form read less

Normalization reduces redundancy. Redundancy is the unnecessary repetition of data. It causes problems with storage and retrieval of data. Redundancy can lead to Inconsistencies, update anomalies etc,. During the process of normalization we can identify dependencies which can cause problems when deleting or updating. Normalization also helps simplify the structure of tables. Normal Forms :- ? First Normal Form (1st NF) ? Second Normal Form (2nd NF) ? Third Normal Form (3rd NF) ? Boyce-Codd Normal Form (BCNF) read less