DBMS/Database Design

entity

nothing but it represents field of the database e.g.,

employee

entity set

collection of different fields

relationship

relationship set

domain

The set of possible values for an attribute is called the

domain of the attribute e.g.: The domain of attribute marital status is having four values: single, married, divorced or widowed.

The domain of the attribute month is having twelve values ranging from January to December.

Key attribute

The attribute (or combination of attributes) that is

unique for every entity instance e.g.: the account number of an account, the employee id of an employee etc.

attribute

e.g., gender

composite attribute

degree of relationship

the number of entity types involved in a

database

cardinality of relationship

The minimum and maximum values of this

connectivity is called the cardinality of the relationship e.g., one to one, one to many, many to many

weak entity

Entity that depends on other entity for its existence and

doesn’t have key attribute (s) of its own e.g. : spouse of employee

identifying relationship

non-identifying relationship

discriminator

ER Diagram

• entity relationship data model
• Introduction to Data Modeling at University of Texas, Austin

Modelling concepts

• Specialisation
• Generalisation
• Categorisation
• Aggregation

Normalization

Normalization is the formal process for deciding which attributes should

be grouped together in a relation.The process of normalization was 

first developed by E.F.CODD. Normalization is the process of evaluating and correcting the relation schemes to minimize data redundancies and thereby reducing anomalies.

First Normal Form

As per the rule of the 1NF an attributes of a table cannot hold multiple value. It should hold only atomic value.

Second Normal Form

Second Normal form is characterized by the property of functional dependency. a relation is in second normal form if it is in 1st normal form and every non key attribute is fully and functionally dependent on the primary key.

Third Normal Form

transitive dependency : A relation is in third normal form , if it is in second normal form and

no transitive dependencies exist.

Suppose A,B and C are the three attributes of a relation(R) then if A->B(B depends on A) B->C(C depends on B) then we can say that "C" depends transitively on "A".

Boyce Codd Normal Form (BCNF)

BCNF is based on functional dependencies that take into account all candidate keys in a relation. For a relation with only one candidate key, 3rd normal form and BCNF are equivalent. A relation is in BCNF if and only if every determinant is a candidate

key.

'''' now what is a determinant? consider the following functional dependency: A→B where A and B are attributes in relation R. it says that B is functionally dependent on A. here A is referred to as determinant and B is the dependent.

BCNF is slightly stronger than 3nF.

Fourth Normal Form

multivalued dependencies are removed

Fifth Normal Form

Any remaining anomalies are removed.in this normal form we isolate semantically related multiple relationships.

Anomalies can be : Insertion Anomaly,Deletion Anomaly or Modification/update Anomaly. Any remaining anomalies are removed.in this normal form we isolate semantically related multiple relationships.