1. PRANVEER SINGH INSTITUTE
OF TECHNOLOGY
NH-2 BHAUTI, KANPUR
PROFESSIONAL COMMUNICATION
PROJECT WORK
Presentation by:- Under Guidance of
Praveen Srivastava Mrs. Raavee Tripathi
CS - 1 A
Roll No:1116410111
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CONTENTS
 INTRODUCTION
 PURPOSE OF DBMS
 DATABASE
ABSTRACTION
 DATA MODELS
 THE RELATIONAL
MODEL
 COMPARISIONOF
DATA MODELS

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INTRODUCTION
A database may be defined as a
collection of interrelated data stored
together to serve multiple applications
A database system is basically a computer based
record keeping system. The collection of data,
usually referred to ac the database, contains
information about one particular enterprise. It
maintains any information that may be necessary
to the decision-making processes involved in the
management of that organization.

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Purpose of DBMS
• Database reduce the data redundancy to
a large extent.
• Databases can control data inconsistency
to a large extent.
• Database facilitate sharing of data.
• Database enforce standards.
• Database can ensure data security.
• Integrity can be maintained through
database.

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DATABASE ABSTRACTION
• Levels of Database Implementation.
1. Internal Level
2 . Conceptual Level
3 . External Level
• Data Independency.
The ability to modify a scheme definition in one level without
affecting a scheme definition in the next higher level is called
Data independency.

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DATA MODELS
• The Relational Data Model.
In relational data model, the data is organized into tables {i.e., rows $
column}
• The Network Data Model.
In network model, data is represented by collections of record $
relationships among data are represented by links.
• The Hierarchical Data Model.
The only difference between hierarchical $ relational data
model is that, records are organized as trees rather
than arbitrary graph.

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THE RELATIONAL
MODEL
1. Terminology
• Relation : It is a table i.e., data is arranged in rows
and columns.
• Domain : It is a pool of values from which the actual
values appearing in a given column are drawn.
• Tuple : The rows of tables (relation) are generally
referred to as Tuple.
• Attribute : The columns of a table (relation) are
generally referred to as attribute.
• Degree : The number of attributes in a relation.
• Cardinality : The number of tuples in a relation.

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2. VIEWS
A view is a (virtual) table that does not really exist
in its own right but is instead derived from one or
more underlying base table(s).
3. Structure of Relational
Databases
• Keys
a)Primary key: It is a set of one or more attributes
that can uniquely identify tuples within the relation.
b)Canditate key: All attribute combinations inside a
relation that can serve as primary key are candidate
keys as they are candidates for the primary key
position.

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c) Alternate key : A candidate key that is not the
primary key is called an alternate key.
d) Foreign key : A non-key attribute, whose values are
derived from the primary key of some other table, is
known as foreign-key in its current table.
• Referential integrity
It is a system of rules that a DBMS uses to ensure
that relationships between records in related tables are
valid, and that users don’t accidentally delete or change
related data.

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Comparison of Data Models
Data models can be evaluated on the basis of usability,
implementability and performance.
Data experts have been debating for some time which
DBMS data model is ‘best’. The answer depends, in part,
on philosophical orientation. The hierarchical model is
the oldest model and has long been the most popular on
mainframes. People who think the user should be able to
have some control over the details of storage allocation
and search paths often prefer network systems.
However, few database systems are fully relational.
Instead they graft relational features on a basic
hierarchical or network structure.

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Information plays an important
role in management of the
building systems and the DBMS
is providing information and
updates and supplies relevant
multi-user information to the
concerned users. Based on the
statistics the DBMS will provide,
through out the year major
planning could be done and that
could lead deriving parameters
for AI Techniques and fuzzy logic
which could make the building
system more efficient and
responsive to the human needs
and comfort.

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