Lecture Notes in Database Management Systems

This document provides lecture notes on database management systems, covering topics such as introduction to DBMS, data abstraction, instances and schemas, data models, database design, data storage and querying, transaction management, data mining and information retrieval, and classification of DBMS.

Lectures Notes in
Database Management Systems
Lecture (2)
Submitted By:
Dr. Ahmed Mohamed Abd-Elwahab
Lecture in BIS Department,
Faculty of Commerce & Business Administration,
Helwan University, Cairo, Egypt.

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Ch 1. Introduction to DBMS
OUTLINE (Part One)
❑ Introduction.
❑ Basic Definitions.
❑ Purpose of Database Systems.
❑ Disadvantages of the File Processing Systems.
❑ Main Characteristics (Advantages) of the Database Sy
❑ Database Systems Applications.

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لكشب تانايبال نيزختمظنموترمب
تانايبال عاجرتساةعرسبوةلوهسوقدة

Flat File Environment
File Processing Database System

5

6

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CHAPTER (1) Cont.
Introduction to DBMS

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Ch 1. OUTLINE (Part Two)
❑ Data Abstraction.
❑ Instances and Schemas.
❑ Data Models Categories.
❑ Database Design.
❑ Data Storage and Querying.
❑ Transaction Management.
❑ Data Mining & Information Retrieval.
❑ Classification of DBMS.

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1.6 Data Abstraction
Forthe System to be usable,it mustretrieve data
efficiently.The need for efficiency has led designers
use Complex data structures to represent data
database.Since many database systems users are no
computertrained,developershide the Complexity
from users through SeveralLevels ofAbstraction,to
simplify Users'interactions with the System.
al user mesh sh8l balo b 7aga
lma al klam bta3 al mibile yakmle al klam ale ana ktbah

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Data Abstraction in DBMS is a
Processof hidingirrelevant
detailsfrom Users.Because
database systemsare made of
Complex data structures.so,it
makes accessiblethe user
interaction with the database.

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1.6 Data Abstraction
The Three Levels of Data Abstraction:
describe how to storage data
nahtm bl data nafsha wl reltion ships

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1.6 Data Abstraction
1.Physical Level:
The Lowest-Level of abstraction describ
➢ How the data are actually Stored.
➢ Complex low-level data structures in de

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1.6 Data Abstraction
2. Logical Level:
The Next Higher-Level of abstraction des
➢ What data are stored in the database.
➢ What relationships exist among those data.
Database Administrators,who must decide what information
to keep in the database, use the logical level of abstract
consabtion level

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1.6 Data Abstraction
3. View level:
The Highest-Levelof abstractiondescribes
Only Part of the entire Database to simplif
interaction between Users with the System
Even though the logicallevelusessimplerstructures,complexity
remainsbecauseof thevariety ofinformation stored in a large
database.Many usersof the database system do notneed allthis
information; instead, they need to access only a part of the data

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1.7 Instances and Schemas
❑ Instance of the Databaseis the collection of
information stored in thedatabaseat a
particular moment (Snapshot of the da
❑ Database Schemais the Overalldesign of
the database (logical design).A schema is a
collection of Objects (Entities) that prov
a logical classification of objects in the dat
lama aft7 al dolab w abos basa srea ana m7tag ah w mesh m7tag ah w ah ale gwa
sora mos8ra

17

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1.7 Instances and Schemas
❑ A Schemais also anObjectin thedatabase.
A database schema can be divided
broadly into two categories:
1. Physical Database Schema:
Describes the Database Design
at the Physical Level.
2. Logical Database Schema:
Describes the Database Design
at the Logical Level.
3. Subschema:
Describes different views of
the Database.
entity
mesh mhma

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1.8 Data Models
❑ Data Modelis a collection of Conceptua
toolsfor describingdata,relationship
between data and constraints.
❑ Data Modelshelp in describingthe
Structure of the Database.
quere ya3ne astslam aw astfsar 3n 7aga

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1.8 Data Models Categories
The DATA MODELS can be classified int
Four different categories:
1. Relational Model.
2. Entity Relationship Model.
3. Object Based Data Model.
4. Semi Structured Data Model.
tables
er diagram colection od entities
stucturre ya3ne arkam w 7rof 3wz ta5znha un structured vedios w oudios
ama hana ban al bnan semmi

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1. Relational Model
TheRelationalModelusesa collection of
tables = (Relations) to represent both da
the relationships among those data.
➢ Each table (Relation) has multiple columns,and each column
has aunique name.
➢ The Relational Model is an example of a Record-Based
➢ Record-Based Models are so named because the databa
structured in Fixed-format Records = Tuples = Rows.
1.8 Data Models Categories

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1.8 Data Models Categories
1. Relational Model
Columns
=
Table =
Row
=
Record

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1.8 Data Models categories
2. Entity Relationship Model
The Entity Relationship (ER) Data Mode
a collection of basic Entities (Objects), and the
relationships among these objects.
➢ An Entity is a “thing” or “object” in the real w
that is distinguishable from other objects.
➢ The ER model is widely used in database desi
mesh han2ol relations
d 5ls han2ol bdlha entites

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1.8 Data Models categories
2. Entity Relationship Model

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3. Object Based Data Model
➢ Object Oriented Programming
(Especiallyin Java,C++,or C#) hasbecomethedominant
software development methodology.
➢ Object Oriented Data Model
Extendingthe E-R modelwith notionsof Encapsulation,
Methods(functions), Object identity.
➢ Combinesfeaturesof the object-oriented data
model and relational data model.
1.8 Data Models Categories

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1.8 Data Models Categories
4. Semi Structured Data Model
Specification ofdata where individualdata
items ofthe same type may have different
sets of attributes.
➢ Every data item of a particular type must have th
same set of attributes.
➢ The Extensible Markup Language(XML) is widely used
to represent semi structured data.

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1.9 Database Design
❑ DatabaseSystemsare designedto
Manage vast amount of data.
❑ Database Design mainly involves
Design of the Database Schema.

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1.9 Database Design

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1.10 Data Storage and Query
The Functional Components of a Database
can be broadly divided into the Storage Mana
and Query Processor components.
❑ StorageManageris importantbecausedatabase
typically require a large amount of storage space.
❑ Query Manager isimportantbecauseit helpsthe
database system to simplify and facilitate access to d

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1.11 Transaction Managemen
A transaction is a collection of Opera
that Performs a single logical function
database application.

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1.12 Data Mining & IR
❑ Data Mining
➢ Is a Processof discovering knowledge from dat
also called Machine Learning or Statistical An
➢ DM attempts to discover rules and patterns from
data; “Knowledge discovery in Databases”.

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1.12 Data Mining & IR
❑ Information Retrieval (IR)
➢ Is a Software Program/System thatdeals withthe
Organization, Storage, Retrieval, and Evaluationof
information from document repositories;
“Querying of unstructured textual data”.
astrga3
d hya al tare2a
ale bn3ml beha kd

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1.13 Classification of DBMS
❑ Database Management Systemscan be
Classified based on Several criteria, such as:
1. Data Model,
2. User Numbers,
3. Database Distribution.

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1. Classification Based on Data Model
➢ The most popular data model in use today is Relatio
Model.Wellknown DBMSs like:Oracle,SQL Server,DB2
and My SQL.
➢ Other traditionalmodels,such as:HierarchicalData Model
and Network Data Models.
➢ In recentyears, the newer Object-Oriented Data Models
were introduced.This model is a DBMS in which information is
represented in the form of Objects as used in OOP.(OODBMS)
combine DB capabilities with OOP language capabilities.
1.13 Classification of DBMS
b shkl harme

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2. Classification Based on User Number
➢ A DBMS can be classification based on the number o
supports.
❑ It can be a Single-User database system, which suppone
user at a time.
❑ Multi-User database system,which supportsmultipleusers
concurrently.
1.13 Classification of DBMS
mknt al atm maslan

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3. Classification Based on Distribution
➢ ThereareFourmain Distributed Systemsfor database
systems, which can be used to classify the DBMS.
1. Centralized Systems
2. Distributed Database Systems
3. Homogeneous Distributed Database Systems
4. Heterogeneous Distributed Database Systems
1.13 Classification of DBMS
data kolha fe mkan wa7d
fe mwk3 mo5tlfa
kol wa7ed leh dbms

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Classification Based on Distribution:
1. Centralized Systems:
▪ Database and DBMS are stored at a Single Site
is used by Several Other Systems.
1.13 Classification of DBMS

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Classification Based on Distribution:
2. Distributed Database System:
▪ TheactualDatabaseand DBMS aredistributed
from differentSitesthat are connectedby a
Computer Network.
1.13 Classification of DBMS
matwz3a
kol wa7ed leh data base
bt3to w dbms

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Classification Based on Distribution:
3. Homogeneous Distributed Database System
▪ Homogeneous Distributed Database Systems use theSame
DBMSsoftwarefrom MultipleSites. Dataexchange
between these various sites can be handled easily.
1.13 Classification of DBMS
for example libirary information
system by the same vendor

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Classification Based on Distribution:
4. Heterogeneous Distributed Database Syste
▪ In a HeterogeneousDistributed Database Systems, different
SitesmightusedifferentDBMSSoftware,butthereis
additionalcommon softwareto supportdata exchange
between these sites.
1.13 Classification of DBMS
ex: the various library data
base system use the same
machine readable
cataloging (MARC) format
to support library record
data exchange

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Thanks!
Ahmed Mohamed Abd-