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•    Backup and Recovery: In case of some user error, hardware failure, or any catastrophic event, the DBMS
                   can recover the database from the point it was failed.
              •      Integrity: DBMS ensures the correctness of data stored by introducing various integrity constraints. For
                   example, DBMS will ensure that no two employees have the same Aadhaar number.
           Ø   Disadvantages of DBMS:
              •      Initial Cost: Applications based on DBMS involve higher costs of  hardware and DBMS software.
              •    Complexity: As DBMS offers various functionalities, it becomes a large and complex software, requiring
                   training of application developers.
           Ø   Data Model: A data model is a representation of the structure of real-world objects. A data model comprises
              the following components:
              •      Entity: An entity is a real-world object (such as employee and department  in a company) about which
                   data is stored in the database.
              •    Attribute: An attribute defines the characteristics of an entity. For example, employee id, date of birth,
                   address, and salary form attributes of an employee.
              •    Relationship: A relationship specifies how two entities are related to each other. For example, in a ccompany's
                   database  the employee entity is related to the department entity since an employee works in a department.
              •      Constraint:  A  constraint  describes  the  restrictions  imposed  on  the  data  stored.  For  example,  each
                   employee should have a unique Aadhaar number.

           Ø   Relational  Data  Model:  A  relational  database  management  system  (RDBMS)  stores  data  in  the  from  of
              relations, also called tables. A table has the following  characteristics:
              •      Each column of a table represents a unique attribute.

                   ◦ An attribute has a type denoting the type of data in the column.
                   ◦ Value in a column must conform to the attribute type.
              •      Relational schema describes the structure of a relation. It includes the names of attributes of a table,
                   types of attributes, and the constraints on a table.
              •      Degree: No of attributes in the relation is called degree of the relation.
              •    Tuple: A row in a table is called a tuple.
              •    Entity Set: The set of all tuples at a specific time in a relation is known as the entity set.
              •    Relation state, Relation instance: Other names for the  entity set.
              •    Cardinality: Numbers of tuples in the entity set.

              •    Order within a table:
                   ◦ Rows in a table are considered unordered.
                   ◦ Columns in a table are considered unordered.
           Ø   NULL: When value of an attribute is unknown, it is denoted by NULL.
           Ø   Candidate Key: The minimal set of attributes that identifies a tuple in a table is called its candidate key.
              Minimality means that no attribute is superfluous.
           Ø   Primary Key: One of the candidate keys is chosen as primary key.
           Ø   Entity Integrity Constraint: No primary key attribute can have a NULL value
           Ø   Alternate Key: A candidate keys that is not chosen as primary key.
           Ø   Foreign Key: A non-key attribute of table R1 that is part of primary key of table R2 is a foreign key of table R1.
           Ø   Foreign Key Constraint: If a table R1 has a foreign key (say, A)which is part of the primary key of another
              table R2, then
              •      the value  of foreign key A  maybe  be  NULL.
              •      the value  of foreign key A  in table R1 maybe  be non- NULL (say, val). In this case. there must be a
                   tuple  in table R2 having val as the value of the referred attribute.

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