data base manage ment

Database Systems
for BS (IT)
Lecture 1: Introduction
Kaleem ullah
www.grw@pu.edu.pk
Punjab University College of Information Technology

Example:
Robcor company has two divisions and the two
division has 1,380,456 and 1,453,907 invoices,
respectively.
Each invoice has invoice number, date, and
amount
The period is from the first quarter of 1997 to
first quarter of 2002
Total 2,834,363 records
Data versus Information

… … …
3000124 12-Jan-2002 $121.98
… … …
Data
Information:----------?

 Data constitute building blocks of
information
 Information produced by processing
data
 Information reveals meaning of data
 Good, timely, relevant information
key to decision making
 Good decision making key to
organizational survival

Historical Roots of Database
Files and File Systems:
 Why we need to study files and file
system?
 Historically handling data
 Help to understand database design

Historical Roots of Database
Files and File Systems:
 First applications focused on clerical tasks
 Requests for information quickly followed
 File systems developed to address needs
 Data organized according to expected use
 Data Processing (DP) specialists
computerized manual file systems

File Terminology
 Data
 Raw Facts
 Field
 Group of characters with specific meaning
 Record
 Logically connected fields that describe a person,
place, or thing
 File and file folder
 Collection of related records

File System Critique
 File System Data Management
 Requires extensive programming in third-
generation language (3GL): COBOL, Basic, and
Fortran (what must be done and how it is to be
done)
 Time consuming
 depends on physically store data
 Makes ad hoc queries impossible
 Make difficult to modify file system (each file has
its own system)
 Leads to islands of information

File System Critique (con’t.)
 Data Dependence
 Change in file’s data characteristics requires
modification of data access programs
 Must tell program what to do and how to do
 Makes file systems cumbersome from
programming and data management views
 Structural Dependence
 Change in file structure requires modification of
related programs

 Field Definitions and Naming Conventions
 Flexible record definition anticipates reporting
requirements
 Selection of proper field names important
 Attention to length of field names
 Use of unique record identifiers

 Data Redundancy: (Unnecessary Duplication of
data)
 Results of uncontrolled data redundancy
 Data anomalies
 Modification
 Insertion
 Deletion
 Data inconsistency (Different and conflicting versions of same data)
 Lack of data integrity

Database Management
 Database is shared, integrated computer
structure that stores a collection of data:
 End user data (raw data)
 Metadata (data about data, it contains data
characteristics and relationships)

 DBMS is an application, which holds user data permanently
and then provide different operations on this data e.g., retrieval
of data, insertion of data, updation of data etc.
 It is a computerized system whose overall purpose is to
maintain information and to make that information available on
demand.
Database Management System (DBMS)
is just a computerized record-keeping system.
Non-technical
Collection of data in the form of files, electronic filing cabinet
A software or application providing operations on the data like,
adding new files, inserting new data, retrieving existing data,
updating and deleting data,removing files etc.

Database Management
 Database Management System (DBMS):
software system (collect of software) help
to manage the data contents
 Manages Database structure
 Controls access to data
 Contains query language
Application software DBMS Database

Importance of DBMS
• Makes data management more efficient and
effective
• Query language allows quick answers to ad hoc
queries
• Provides better access to more and better-
managed data
• Promotes integrated view of organization’s
operations
• Reduces the probability of inconsistent data
• Improved data sharing
• Improved data security

Important terms and definitions
 Retrieval, Insertion, Deletion, Updation
 Field, Record, Table
 Structured Query Language (SQL)
 Data vs. Information
 Single-user and Multi-user Systems
 Integrated and Shared
 Data Administration
 identifying data and needs of enterprise w.r.t. data, deciding what
data should be stored, establishing policies for maintaining and
dealing with stored data
 Database Administration
 creating actual database and implementing technical controls
needed to enforce policy decisions made by data administrator and
related technical services
 Database users
 Application Programmers
 End Users
 DBA’s

Terms in Relational Model
 Relation
 Tuple, Attribute
 Cardianlity, Degree
 Domain
tuples
attributes
ID Name Age Department
S1 Ahmad 23 Sales
S2 Salman 34 Marketing
S3 Karim 21 Sales
S4 Tariq 29 Admin
S5 Sadiq 32 Sales
Employee Relation
Cardinality
Degree

 Scalar values (Atomic)
 at every row and column position in every table there is always
exaclty one data value
 Repeating Group
A repeating group is a column, or combination of columns that
contain several data values in each row
ID Name Age MarksMax.Marks
• RDBMS does not allow repeating groups
 Optimazation
a system component that determine how to implement
user requests
 Catalog
set of system tables

 Data Sub languages
 DDL
 DML
 DCL
 Query Language
 Schema
 Internal
 External
 Conceptual
 Data Dictionary
 Redundancy
 Client/Server Architecture
 Distributed Processing and Database System
 Security and Integrity
 Backup and Recovery

Jobs of DBA
 Defining Conceptual Schema
 Defining Internal Schema
 Liaising with users
 Defining Security and Integrity rules
 Defining Backup and Recovery procedures
 Monitoring performance and responding to changing
requirements

Why Database Design is Important
 Database design focuses on design of
database structure used for end-user data
 Designer must identify database’s expected use
 Well-designed database:
 Facilitates data management
 Generates accurate and valuable information
 Poorly designed database:
 Causes difficult-to-trace errors

Database Systems
 Database consists of logically related data
stored in a single repository
 Provides advantages over file system
management approach
 Eliminates data inconsistency (lack of data
integrity), data anomalies, data dependency,
and structural dependency problems
 Stores data structures, relationships, and access
paths

Database System Environment
 Hardware
 System’s Physical devices
 Computers
 Peripherals
 Network

 Software
 Operating system: manages hardware
components
 DBMS: manages database
 MS Access, SQL Server, Oracle, DB2
 Application and utility software: support access
and manipulate data
 Generate information for decision making
 Help to manage database system

 People (five users)
 System administrator: hardware system support
 Database administrator: manage DBMS use
 Database designer: design database structure
 System analyst and programmers: implement
application programs
 End users

 Procedures
 Instruction and rule that govern the
design and use of the database
system
 Data

Database System Types
 Single-user vs. Multi-user Database (user
number)
 Desktop database – Single user
 Workgroup database --supports a small number
 Enterprise database --supports a large number
 Centralized vs. Distributed (location)
 Use
 Production or transactional
 Decision support or data warehouse
(obtain information)

DBMS Functions
 Objective: Guarantee the integrity and
consistency of data. It has several functions:
 Data dictionary management: (the definition of the data elements
and their relationships are stored in a data dictionary). It remove
data and structure dependencies.
 Data storage management: structures required for data storage
 Data transformation and presentation: relieving us from the distinct
between logical data format and physical data format
 Security management
 Multiuser access control (concurrency)

DBMS Functions
 Backup and recovery management
 Data integrity management
 Database access language and application
programming interfaces
 Query language (DDL and DML)
 Database communication interfaces

Database Models
 Definition: collection of logical constructs
used to represent data structure and
relationships within the database
 Conceptual models: logical nature of data
representation; it emphasizes on what entity is
presented; it is used for database design as
blueprint
 Implementation models: emphasis on how the
data are represented in the database

Database Models
 Conceptual models include
 Entity-relationship database model (ERDBD)
 Object-oriented model (OODBM)
 Implementation models include
 Hierarchical database model (HDBM)
 Network database model (NDBM)
 Relational database model (RDBM)
 Object-oriented database model (ODBM)

Database Models (con’t.)
 Relationships in Conceptual Models
 One-to-one (1:1)
 One-to-many (1:M)
 Many-to-many (M:N)
 Implementation Database Models
 Hierarchical
 Network
 Relational
 Object-Oriented

Evolution of Database
Modals
1960s
1970s
1990s
Traditional
files
Hierarchical
Network
1980s
Relational
Object oriented
Object-relational
2000s
Client Oriented
?

Hierarchical Database Model (HDBM)
 Logically represented by an upside down tree
 Each parent can have many children (segment
linkage)
 Each child has only one parent
 A single table acts as the "root" of the database
from which other tables "branch" out.
 Relationships in such a system are children and
parents.
 Parents and children are tied together by links
called "pointers

Hierarchical Database Model
 Logically represented by an upside down tree
 1:M relationship

 Hierarchical path (beginning from left)
 Left-list hierarchical path, or preorder traversal, or
hierarchical sequence
 Re-list sequence, if the segment is frequently
accessed
 Bank systems commonly use HD model
Final assembly->Component A->Assembly A-> -> PartFinal assembly->Component A->Assembly A-> -> Part
A ->Part B -> Component B -> Component C –A ->Part B -> Component B -> Component C –
Assembly B -> Part C ->Part DAssembly B -> Part C ->Part D

 Bank systems commonly use the HDBM
 customer account can be subject to
many transactions (1:M relationship)
 Relationship is fixed (debiting and
crediting)
 Frequently access large amount of
transactions

 Advantages
 Conceptual simplicity: relationship between layers is logically
simple; design process is simple
 Database security: enforced uniformly through the system
 Data integrity
 Data independence
 Efficiency in 1:M relationships and when uses require large
numbers of transactions
 Dominant in 1970s , when we used mainframe system with large
databases

 Disadvantages
 Complex implementation: physical data storage
characteristics; database design is complicated
 Difficult to manage and lack of standards
 Lacks structural independence
 Applications programming and use complexity
(pointer based)
 Implementation limitations, i.e. especially it only
handle 1:M type of model

Network Database Model (NDBM)
 Each record can have multiple parents
 Called by Database Task Group (DBTG) to define standards
 Three crucial database components
 Network schema: conceptual organization of the entire
database
 Subschema: portion of database as information for
application programs
 Database management language: defining data
characteristics and data structure
 Schema Data definition language (DDL): define schema components
 Subschema Data definition language
 Data manipulating language: manipulate data content

Network Database Model
 Each record can have multiple parents
 Introduce set to describe relationship
 Each set has owner record and member record, parallel
to parent and child in HDM
 Member may have several owners
 One-ownership
 Hierarchical model is a subset of the network model.
 The network model uses set theory to provide a tree-
like hierarchy.

 Member may have several owners

 Advantages
 Conceptual simplicity, just lime HDM
 Handles more relationship types (but all 1:M
relationship)
 Data access flexibility
 Promotes database integrity
 Data independence
 Conformance to standards

 Disadvantages
 System complexity
(Develop by the Computer programmers
for the Computer Programmers rather
than user)
 Lack of structural independence

Relational Database Model (RDBM)
 Let’s user or database designer to operate
human logical environment
 Perceived by user as a collection of tables for
data storage, while let RDBMS handles the
physical details.
 Tables are a series of row/column intersections
 Tables related by sharing common entity
characteristics
 It allows 1:1, 1:M, M:N relationships

Relational Database Model
 Advantages
 Structural independence: data access path is
irrelevant to database design; change structure will
not affect the database
 Improved conceptual simplicity
 Easier database design, implementation,
management, and use
 Ad hoc query capability with SQL (4GL is added)
 Powerful database management system

Relational Database Model
 Disadvantages
 Substantial hardware and system software
overhead
 Poor design and implementation is made
easy
 May promote “islands of information”
problems

data base manage ment

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data base manage ment