Transcript chap01-db

Relational
Data Base
By
T. El-Shishtawy
Prof. Ass. Of Computer
Engineering
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Chapter 1:
The Database Environment
Modern Database Management
6th Edition
Jeffrey A. Hoffer, Mary B. Prescott, Fred R.
McFadden
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Definitions
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Data:
– Meaningful facts, text, graphics, images, sound, video
segments
– Data are raw facts that constitute building block of
information
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Information:
– Data processed to be useful in decision making
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Metadata:
– Data that describes data
– The data in DBMS can be broadly classified into two
types,
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the collection of information needed by the organization and
“metadata” which is the information about the database.
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Figure 1-1a Data in Context
Large volume of facts, difficult
to interpret or make decisions
based on
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Figure 1-1b Summarized data
Useful information that managers can use for
decision making and interpretation
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Table 1-1 Metadata
Descriptions of the properties or characteristics of the
data, including data types, field sizes, allowable
values, and documentation
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Database
An organized collection of logically related data
– A database is a an organized collection of data that
are related in a meaningful way
– Database systems are systems in which the
interpretation and storage of information are of
primary importance
– Several users can access the data in an organization
still the integrity of the data should be maintained.
– A database is integrated when same information is
not recorded in two places.
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Disadvantages of File Processing
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Prior to DBMS, file system provided by OS was
used to store information
 Program-Data Dependence
– All programs maintain metadata for each file they use
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Data Redundancy (Duplication of data)
– Different systems/programs have separate copies of the same data
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Limited Data Sharing- Incompatible File Formats
– No centralized control of data
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Lengthy Development Times
– Programmers must design their own file formats
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Excessive Program Maintenance
– 80% of of information systems budget
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Figure 1-2 Three file processing systems at Pine
Valley Furniture
Duplicate
Data
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Problems with Data Dependency
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Each application programmer must maintain their
own data
Each application program needs to include code
for the metadata of each file
Each application program must have its own
processing routines for reading, inserting, updating
and deleting data
Lack of coordination and central control
Non-standard file formats
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Problems with Data
Redundancy
 Waste
of space to have duplicate data
 Causes more maintenance headaches
 The biggest Problem:
– When data changes in one file, could cause
inconsistencies
– Compromises data integrity
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Incompatible File Formats
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The structure of the file depends on the
application programming language.
– For example, the structure of the file generated
by FORTRAN program may be different from
the structure of a file generated by “C”
program.
– The incompatibility of such files makes them
difficult to process jointly
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SOLUTION:
The DATABASE Approach
 Central
repository of shared data
 Data is managed by a controlling agent
 Stored in a standardized, convenient
form
Requires a Database Management System (DBMS)
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Database Management
System

A DBMS is a data storage and retrieval
system which permits data to be stored nonredundantly while making it appear to the
user as if the data is well-integrated.
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Database Management System

A DBMS consists of: A collection of interrelated and
persistent data. This part of DBMS is referred to as
database (DB).
 A set of application programs used to access,
update, and manage data. This part constitutes
data management system (MS).
 A DBMS is general-purpose software i.e., not
application specific. The same DBMS (e.g., Oracle,
Sybase, etc.) can be used in railway reservation
system, library management, university, etc.
 A DBMS takes care of storing and accessing data,
leaving only application specific tasks to application
programs.
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Database Management System
Application
#1
Application
#2
Application
#3
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DBMS
Database
containing
centralized
shared data
DBMS manages data
resources like an operating
system manages hardware
resources
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Advantages of Database Approach
 Program-Data
Independence
– Metadata stored in DBMS, so applications don’t need to worry
about data formats
– Data queries/updates managed by DBMS so programs don’t
need to process data access routines
– Results in: increased application development and maintenance
productivity
 Minimal Data Redundancy
– Leads to increased data integrity/consistency
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Advantages of Database Approach
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Improved Data Sharing
– Different users get different views of the data
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Enforcement of Standards
– All data access is done in the same way
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Improved Data Quality
– Constraints, data validation rules
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Better Data Accessibility/ Responsiveness
– Use of standard data query language (SQL)
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Security, Backup/Recovery, Concurrency
– Disaster recovery is easier
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Notes
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Data redundancy
– duplication of data. Data redundancy will
occupy more space hence it is not desirable.
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Data independence
– independence between application program and
the data. The advantage is that when the data
representation changes, it is not necessary to
change the application program.
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Data inconsistency
– different copies of the same data will have
different values.
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Notes
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Centralizing the data
– data can be easily shared between the users but the
main concern is data security.
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The main threat to data integrity comes from
– several different users attempting to update the same
data at the same time.
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Support for multiple views means
– DBMS allows different users to see different
“views” of the database, according to the
perspective each one requires. This concept is used
to enhance the security of the database.
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Costs and Risks of the
Database Approach
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Up-front costs:
– Installation Management Cost and Complexity
– Conversion Costs
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Ongoing Costs
– Requires New, Specialized Personnel
– Need for Explicit Backup and Recovery
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Organizational Conflict
– Old habits die hard
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Data Abstarction
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The main objective of DBMS is to store and
retrieve information efficiently.
 It is not necessary for the users to know
physical database storage details
The developers hide the complexity from users
through several levels of abstraction
– 1. Physical level or internal level
– 2. Logical level or conceptual level
– 3. View level or external level
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Data Abstarction
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Database Schema
The overall design of the database is called the
database schema
A schema can contain tables, views, triggers,
functions, packages, and other objects.
Physical schema
– Describes the Database Design at the Physical level
Logical schema
– Describes the database design at the logical level
Subschema
– Describes different views of the database
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Data Models
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Data model is collection of conceptual tools for describing
data, relationship between data, and consistency constraints
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Figure 1-3 Segment from enterprise data model
Figure 3
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People Interacting with
Database
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Database Administrator
 A person having central control over data and programs accessing
that data.
 The objectives of database administrator are
– To control the database environment
– To standardize the use of database and associated software
– To support the development and maintenance of database.
 The responsibilities of the database administrator are:
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Authorizing access to the database.
Coordinating and monitoring its use.
Acquiring hardware and software resources as needed.
Backup and recovery.
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Database Designer
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Database designer can be either logical database
designer or physical database designer.
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Logical database designer is concerned with
identifying the data, the relationships between
the data, and the constraints on the data
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The physical database designer takes the logical
data model and decides the way in which it can
be physically implemented
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Database Users
Database users are the people who need
information from the database to carry out their
business.
Can be classified into :
– application programmers
– and end users.
Application programmers write application
programs and interacts with the data base
through host Language like Pascal, C , SQL
and Cobol
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Data Dictionary or system
catalog
 It contains information about the database
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tables,
the fields of the tables,
data types,
primary keys, foreign keys
indexes,
 It can be considered as a file that stores Metadata
 One of its major functions
– to enforce the constraints placed upon the database by the
designer,
 such as referential integrity and cascade delete.
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Functional Components of Database
System Structure
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1- Storage manager.
– It is responsible for storing, retrieving, and updating
data in the database. Storage manager components
are:
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1. Authorization and integrity manager.
2. Transaction manager.
3. File manager.
4. Buffer manager.
2. Query processor.
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1- Authorization and Integrity Manager
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Checks the integrity constraints and
authority of users to access data.
 DBMS can ignore storing or updating data
due to
– Authority Violation, or
– Constraints Violation
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2- Transaction Management
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A transaction is a collection of operations that
performs a single logical function in a database
application.
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Transaction-management component ensures that the
database remains in a consistent state despite system
failures and transaction failure.
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Concurrency control manager controls the interaction
among the concurrent transactions, to ensure the
consistency of the database
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3- File Manager
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File manager manages the allocation of
space on disk storage.
 The file manager can:
– – Create a file
– – Delete a file
– – Update the record in the file
– – Retrieve a record from a file
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Database Architecture

The database architecture can be broadly
classified into two-, three-, and multitier
architecture.
 Two-Tier Architecture
– two-tier architecture is a client–server
architecture
– The client contains the presentation code and
the SQL statements for data access.
– The database server processes the SQL
statements and sends query results back to the
client
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Figure 1-8 Client server
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Two-Tier Architecture
Advantages of Two-tier Architecture
– is a good approach for moderate number of
clients.
– is the simplest to implement, due to the number
of good commercial development environments.
Drawbacks of Two-tier Architecture
– Software maintenance can be difficult
PC clients contain a mixture of presentation,
validation, and business logic code.
– the performance of two-tier architecture can be poor
when a large number of clients submit requests
database server may be overwhelmed with managing
messages.
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Three-tier Architecture
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Provides greater application scalability,
lower maintenance, and increased reuse of
components.
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Through standard tiered interfaces, services
are made available to the application.
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Multiple-tier architectures provide more
flexibility on division of processing
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Three-tier Architecture
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Figure 1-5
Client/server
system for
Pine Valley
Furniture
Company
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Multitier Architecture

N-tier implementation employs a three-tier
logical architecture superimposed on a
distributed physical model
 Application Servers can access other
application servers in order to supply
services to the client application as well as
to other Application Servers
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Multitier Architecture
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The Range of
Database Applications
Personal Database – standalone desktop
database
 Workgroup Database – local area network
(<25 users)
 Department Database – local area network
(25-100 users)
 Enterprise Database – wide-area network
(hundreds or thousands of users)
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Figure 1-7
Typical data
from a
personal
computer
database
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Figure 1-9 An
enterprise
data
warehouse
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Components of the
Database Environment
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CASE Tools – computer-aided software engineering
Repository – centralized storehouse of metadata
Database Management System (DBMS) – software for
managing the database
Database – storehouse of the data
Application Programs – software using the data
User Interface – text and graphical displays to users
Data Administrators – personnel responsible for maintaining
the database
System Developers – personnel responsible for designing
databases and software
End Users – people who use the applications and databases
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Figure 1-10
Components
of the
database
environment
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Evolution of DB Systems
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Flat files - 1960s - 1980s
Hierarchical – 1970s - 1990s
Network – 1970s - 1990s
Relational – 1980s - present
Object-oriented – 1990s - present
Object-relational – 1990s - present
Data warehousing – 1980s - present
Web-enabled – 1990s - present
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