Normalization in DBMS
In this tutorial, we will study What is Normalization in DBMS, Different types of anomalies (w/o Norm.) Functional Dependency (FD) & its Types and Normal Forms.
What is Normalization in DBMS
Normalization in DBMS is the systematic, step-by-step process of organizing the data in the database in such a way that it minimizes the redundancy from a table or whole database. It is also used to eliminate undesirable characteristics like Insertion, Update, and Deletion Anomalies.
What is the role of Normalization in database design?
To reduce redundancy from the database or individual table.
How to achieve Normalization?
By dividing the larger table into the smaller table and linking them using relationship.
What are the normal forms and their types?
For a table to be in certain normal form it has followed certain rules; if it does so then the table is said to be in that particular normal form. Its types are 1st, 2nd, 3rd & Boyce-Codd Normal form.
What are anomalies and their types?
Relations that have redundant data may have problems called anomalies. They can of type: Insertion, Update, and Deletion Anomalies.
Different types of anomalies (w/o Norm.)
Insertion anomalies – When a tuple/record is tried to be inserted in referencing relation without it being present in the referenced table; it will cause an Insertion Anomaly.
Deletion & Update/ Modification anomalies – When a tuple is deleted or updated from referenced relation and the referenced attribute value is used by referencing attribute in referencing relation, it will not allow deleting the tuple from referenced relation. To avoid such a situation: ON UPDATE/DELETE (SET NULL/CASCADE) is used for setting referenced attribute null or update/delete affected record/row/tuple.
To completely understand the concept of Normalization and normal forms, we need to understand what functional dependency is. So, let’s dive in:
Functional Dependency (FD) & its Types
It describes the interrelation of columns within a table; i.e. when values in one field depend on 1 or more other fields within the same table.
For example, there’s a table/ relation to store data of people within a locality who are eligible to get a driving license. The structure of the table is: (name, age, eligibility). It is clearly known that the field eligibility depends on the age of the person, so “eligibility” is functionally dependent on “age”. (age-> eligibility)
FD can be of types: Trivial (where 1 is a subset of other) and Non-trivial (when related field/s are not subsets of other). Another possible type is Transitive dependency (col1 ->col2 -> col3 indicates that if we know col1, col2 could be known, and if we know col2, col3 could be known.
Normal Forms 1st Normal Form (1 NF)
A relation is said to be in 1NF if it contains an atomic value for every attribute in a record, i.e. no attribute can be multi-valued.
Conversion Step needed: To enter multi-valued attributes in multi-rows by copying other single valued attributes.
2nd Normal Form (2 NF)
2 NF is a relation that is in 1 NF and every non-primary-key attribute is fully functionally dependent on the primary key. This conversion involves the removal of partial dependencies.
Conversion Step needed: Remove FD attributes from the table and place them in a new table.
3rd Normal Form (3 NF)
A relation is said to be in 3NF if it is in 2 NF and no non-primary-key attribute is transitively dependent on the primary key. This conversion involves removal of transitive dependencies if any.
Conversion Step needed: To remove transitive dependency. Eg: address (Line 1,2,3, Street, City, State, PIN code) need to be made as different table and indexed as a unique value and not included directly into Person/ Student/ Employee table.
Boyce-Codd Normal Form (BCNF)
A relation is said to be in BCNF if it is in 3 NF and for each functional dependency (X → Y), X should be a super Key.
Read More: Use My Notes
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ABOUT THE AUTHOR
This Tutorial providing by Technical Education.