Unit 2 DATABASE ESSENTIALS.pptx

Unit 2-Database Essentials
DR. V. NIRMALA
DEPARTMENT OF AI & DS
EASWARI ENGINEERING COLLEGE

Introduction
• A database-management system (DBMS) is a collection of interrelated data and a set of
programs to access those data.
• The collection of data, usually referred to as the database, contains information relevant to an
enterprise.
• The primary goal of a DBMS is to provide a way to store and retrieve database information that
is both convenient and efficient
• Database systems are designed to manage large bodies of information.
• In addition, the database system must ensure the safety of the information stored, despite
system crashes or attempts at unauthorized access. Because information is so important in most
organizations, computer scientists have developed a large body of concepts and techniques for
managing data.

Database-System Applications
1. Enterprise Information
Sales: For customer, product, and purchase information.
Accounting: For payments, receipts, account balances, assets and other accounting information.
Human resources: For information about employees, salaries, payroll taxes, and benefits, and for generation of paychecks.
Manufacturing: For management of the supply chain and for tracking production of items in factories, inventories of items in warehouses
and stores, and orders for items
2. Banking and Finance :
Banking: For customer information, accounts, loans, and banking transactions.
Credit card transactions: For purchases on credit cards and generation of monthly statements.
Finance: For storing information about holdings, sales, and purchases of financial instruments such as stocks and bonds; also for storing real-
time market data to enable online trading by customers and automated trading by the firm.
3. Universities: For student information, course registrations, and grades (in addition to standard enterprise information such as human
resources and accounting).
4. Airlines: For reservations and schedule information. Airlines were among the first to use databases in a geographically distributed manner.
5. Telecommunication: For keeping records of calls made, generating monthly bills, maintaining balances on prepaid calling cards, and
storing information about the communication networks

Purpose of Database Systems
• Earlier in 1960’s they used file processing system tog store, manage and retrieve the data.
• Needs the help of system programmer to run the application programs to modify, edit and retrieve
files.
•Keeping organizational information in a file-processing system has a number of major disadvantages:
• Data redundancy and inconsistency: Duplication of file (student basic inform) need high storage space, change
of data will not be reflected in all files(address change).
• Difficulty in accessing data (needs specific application program for each accessing of file)
• Data isolation. Because data are scattered in various files, and files may be in different formats, writing new
application programs to retrieve the appropriate data is difficult.
• Integrity problems:
• Atomicity Problem: It is difficult to ensure atomicity in a conventional file-processing system, it must happen in
its entirety or not at all (eg: transfer of fund)
• Security problems: Application programs are added to the file-processing system in an ad hoc manner,
enforcing such security constraints is difficult.

View of Data
Abstract view of the data.
That is, the system hides certain details of how the data are stored and
maintained
For the system to be usable, it must retrieve data efficiently. The need for
efficiency has led designers to use complex data structures to represent data in
the database. Since many database-system users are not computer trained,
developers hide the complexity from users through several levels of
abstraction, to simplify users’ interactions with the system
• Physical level. The lowest level of abstraction describes how the data are
actually stored. The physical level describes complex low-level data structures
in detail.
• Logical level. The next-higher level of abstraction describes what data are
stored in the database, and what relationships exist among those data. The
logical level thus describes the entire database in terms of a small number of
relatively simple structures.
• View level. The highest level of abstraction describes only part of the entire
database.
• The view level of abstraction exists to simplify their interaction with the system.
• The system may provide many views for the same database

View of Data…
• At the physical level, an instructor, department, or student record
can be described as a block of consecutive storage locations. The
compiler hides this level of detail from programmers. Similarly, the
database system hides many of the lowest-level storage details
from database programmers. Database administrators, on the
other hand, may be aware of certain details of the physical
organization of the data.
• At the logical level, each such record is described by a type
definition, as in the previous code segment, and the
interrelationship of these record types is defined as well.
Programmers using a programming language work at this level of
abstraction. Similarly, database administrators usually work at this
level of abstraction.
• Finally, at the view level, computer users see a set of application
programs that hide details of the data types. At the view level,
several views of the database are defined, and a database user
sees some or all of these views.
For example, we may describe a record as follows:
This code defines a new record type called instructor with four
fields. Each field has a name and a type associated with it.
A university organization may have several such record types,
including
• department, with fields dept name, building, and budget
• course, with fields course id, title, dept name, and credits
• student, with fields ID, name, dept name, and tot cred

Data Models
•Underlying the structure of a database is the data model: a collection of conceptual tools for describing data, data
relationships, data semantics, and consistency constraints.
•A data model provides a way to describe the design of a database at the physical, logical, and view levels
•The data models can be classified into four different categories:
1. Relational Model.
◦ The relational model uses a collection of tables to represent both data and the relationships among those data.
◦ Each table has multiple columns, and each column has a unique name.
◦ Tables are also known as relations.
◦ The relational model is an example of a record-based model.
◦ Record-based models are so named because the database is structured in fixed-format records of several types. Each table
contains records of a particular type.
◦ Each record type defines a fixed number of fields, or attributes.
◦ The columns of the table correspond to the attributes of the record type.
◦ The relational data model is the most widely used data model, and a vast majority of current database systems are based
on the relational model.

Data Models…
2. Entity-Relationship Model.
◦ The entity-relationship (E-R) data model uses a collection of basic objects, called entities, and relationships among these
objects.
◦ An entity is a “thing” or “object” in the real world that is distinguishable from other objects.
◦ For example, each person in a university is an entity. An entity has a set of properties, and the values for some set of
properties may uniquely identify an entity.
◦ For instance, a person may have a person id property whose value uniquely identifies that person.
3. Object-Based Data Model.
◦ Object-oriented programming (especially in Java, C++, or C#) has become the dominant software-development methodology.
This led to the development of an object-oriented data model that can be seen as extending the E-R model with notions of
encapsulation, methods (functions), and object identity.
◦ The object-relational data model combines features of the object-oriented data model and relational data model.
4. Semistructured Data Model.
◦ The semistructured data model permits the specification of data where individual data items of the same type may have
different sets of attributes.
◦ This is in contrast to the data models mentioned earlier, where every data item of a particular type must have the same set of
attributes.
◦ The Extensible Markup Language (XML) is widely used to represent semistructured data.

Database Languages
•A database system provides a data-definition language to specify the database schema and a
data-manipulation language to express database queries and updates.
•In practice, the data-definition and data-manipulation languages are not two separate
languages; instead they simply form parts of a single database language, such as the widely used
SQL language.
•Data-Manipulation Language
• A data-manipulation language (DML) is a language that enables users to access or manipulate data as
organized by the appropriate data model.
• The types of access are:
• Retrieval of information stored in the database
• Insertion of new information into the database
• Deletion of information from the database
• Modification of information stored in the database

Database Languages..
• There are basically two types:
• Procedural DMLs require a user to specify what data are needed and how to get those
data.
• Declarative DMLs (also referred to as nonprocedural DMLs) require a user to specify
what data are needed without specifying how to get those data.
• A query is a statement requesting the retrieval of information. The portion of a DML that involves information
retrieval is called a query language.
•Data-Definition Language
• We specify a database schema by a set of definitions expressed by a special language called a data-definition
language (DDL).
• The data values stored in the database must satisfy certain consistency constraints. For example, suppose the
university requires that the account balance of a department must never be negative. The DDL provides
facilities to specify such constraints. The database system checks these constraints every time the database is
updated.

Database Architecture
•The architecture of a database system is
greatly influenced by the underlying computer
system on which the database system runs.
Database systems can be centralized, or client-
server, where one server machine executes
work on behalf of multiple client machines.
•Database applications are usually partitioned
into two or three parts, as in Figure.
•In a two-tier architecture, the application
resides at the client machine, where it invokes
database system functionality at the server
machine through query language statements.

Database Architecture..
•In a three-tier architecture, the client machine
acts as merely a front end and does not
contain any direct database calls. Instead, the
client end communicates with an application
server, usually through a forms interface. The
application server in turn communicates with
a database system to access data.
•Three-tier applications are more appropriate
for large applications, and for applications that
run on the World Wide Web.

Relational Model
•Relational model can represent as a table with
columns and rows. Each row is known as a
tuple/ record. Each table of the column has a
name or attribute.
•A relational database consists of a collection of
tables, each of which is assigned a unique
name. For example, consider the instructor
table, which stores information about
instructors. The table has four column
headers: ID, name, dept name, and salary.
Each row of this table records information
about an instructor, consisting of the
instructor’s ID, name, dept name, and salary.

Relational Model..
• Similarly, the course table of Figure stores information about courses, consisting of a course
id, title, dept name, and credits, for each course. Note that each instructor is identified by the
value of the column ID, while each course is identified by the value of the column course id
• In general, a row in a table represents a relationship among a set of values. Since a table is a
collection of such relationships, there is a close correspondence between the concept of table
and the mathematical concept of relation, from which the relational data model takes its
name. In mathematical terminology, a tuple is simply a sequence (or list) of values. A
relationship between n values is represented mathematically by an n-tuple of values, i.e., a
tuple with n values, which corresponds to a row in a table.
• Thus, in the relational model the term relation is used to refer to a table, while the term tuple
is used to refer to a row. Similarly, the term attribute refers to a column of a table.
• Relational instance:
• We use the term relation instance to refer to a specific instance of a relation, i.e., containing a
specific set of rows. The instance of instructor shown has 12 tuples, corresponding to 12
instructors
• In the relational database system, the relational instance is represented by a finite set of tuples.
Relation instances do not have duplicate tuples
• Domain:
• For each attribute of a relation, there is a set of permitted values, called the domain of that
attribute.
• Thus, the domain of the salary attribute of the instructor relation is the set of all possible salary
values, while the domain of the name attribute is the set of all possible instructor names.
• It contains a set of atomic values that an attribute can take.

Unit 2 DATABASE ESSENTIALS.pptx

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Unit 2 DATABASE ESSENTIALS.pptx