Ch09 DBMS (Revised 20071206)

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Chapter 9

Database Management Systems

Accounting Information Systems, 5th editionJames A. Hall

(Revised by Jiin-Feng Chen, National Chengchi University forclassroom use)

COPYRIGHT 2007 Thomson South-Western, a part of The Thomson Corporation. Thomson, the Star logo,and South-Western are trademarks used herein under license

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Objectives for Chapter 9

Problems inherent in the flat file approach to datamanagement that gave rise to the database concept

Relationships among the defining elements of the

database environment Anomalies caused by un-normalized databases and the

need for data normalization

Stages in database design: entity identification, data

modeling, constructing the physical database, andpreparing user views

Features of distributed databases and issues to considerin deciding on a particular database configuration

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Flat-File Versus Database

Environments

Computer processing involves two components: dataand instructions (programs).

Conceptually, there are two methods for designing theinterface between program instructions and data:

file-oriented processing: A specific data file wascreated for each application

data-oriented processing: Create a singledatarepository to support numerous applications.

Disadvantages of file-oriented processing includeredundant data and programs and varying formats forstoring the redundant data.

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Flat-File Environment

Program 1

Program 2

Program 3

A,B,C

X,B,Y

L,B,M

User 2

Transactions

User 1Transactions

User 3

Transactions

Data

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Data Redundancy &Flat-File Problems

Data Storage - creates excessive storage costs

of paper documents and/or magnetic form Data Updating - any changes or additions mustbe performed multiple times

Currency of Information - potential problem of

failing to update all affected files Task-Data Dependency - users inability to

obtain additional information as his or herneeds change

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Program 1

Program 2

Program 3

User 2

Transactions

User 1Transactions

User 3

Transactions

Database

D

BMS

A,B,

C,X,Y,L,

M

Database Approach

Applications

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Advantages of the

Database ApproachData sharing/centralizeddatabase resolves flat-file problems:

Nodata redundancy-Data is stored only once, eliminating

data redundancy and reducing storage costs. Single update-Because data is in only one place, it

requires only a single update, reducing the time and cost ofkeeping the database current.

Current values-A change to the database made by any

user yields current data values for all other users. Task-data independence-As users information needs

expand, the new needs can be more easily satisfied thanunder the flat-file approach.

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Disadvantages of the

Database Approach Can be costly to implement

additional hardware, software, storage, and networkresources are required

Can only run in certain operating environments may make it unsuitable for some system

configurations

Because it is so different fromthe file-oriented approach, the databaseapproach requires training users may be inertia or resistance

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Elements of the Database Approach

System Development

Process

DatabaseAdministrator

USERS

DBMS

HostOperatingSystem

PhysicalDatabase

User

Programs

UserPrograms

UserPrograms

Applications

DataDefinitionLanguage

DataManipulationLanguage

QueryLanguage

User Queries

Transactions

Transactions

Transactions

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DBMS Features User Programs - makes the presence of the DBMS

transparent to the user

Direct Query - allows authorized users to accessdata without programming

Application Development - user createdapplications

Backup and Recovery - copies database

Database Usage Reporting - captures statistics ondatabase usage (who, when, etc.)

Database Access - authorizes access to sections ofthe database

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Internal Controls and DBMS

The purpose of the DBMS is to provide

controlled accessto the database. The DBMS is a special software system

programmed to know which data elements

each user is authorized to access anddeny unauthorized requests of data.

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Data Definition Language (DDL)

DDL is a programming language used to definethe database to the DBMS.

The DDL identifies the names and the relationship

of all data elements, records, and files thatconstitute the database. Viewing Levels:

internal view - physical arrangement of

records (1) conceptual view - representation of database(1)

user view - the portion of the database eachuser views (many)

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Data Manipulation Language (DML)

DML is the proprietary programminglanguage that a particular DBMS uses to

retrieve, process, and store data.

Entire user programs may be written in theDML, or selected DML commands can be

inserted into universal programs, such asCOBOL and FORTRAN.

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Query Language

The query capability permits end usersand professional programmers to access

data in the database without the need forconventional programs.

ANSIs Structured Query Language (SQL)

is a fourth-generation language (4GL) thathas emerged as the standard querylanguage.

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Functions of the DBA

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Logical Data Structures

A particular method used to organize records ina database is called the databases structure.

The objective is to develop this structureefficiently so that data can be accessed quicklyand easily.

Four types of structures are:

hierarchical (tree structure) network

relational

object-oriented

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The Relational Model

The relational model portrays data in theform of two dimensional tables:

relation - the database table

attributes (data elements) - form columns

tuples (records) - form rows

data - the intersection of rows and columns

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RESTRICT - filtering out rows,such as the dark blue

PROJECT - filtering out columns,such as the light blue

X1 X1

X2 X2

X3 X3

Y1

Y1

Y1 Y1

Y1

Y2 Y2 Y2

Y3

Z1 Z1

Z2 Z2

Z3 Z1

JOIN

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Properly Designed Relational Tables

No repeating values - All occurrences at theintersection of a row and column are a single

value. The attribute values in any column must all

be of the same class.

Each column in a giventable must beuniquely named.

Each row in the table must be unique in atleast one attribute, which is the primary key.

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Crows Feet Cardinalities

(1:0,1)

(1:1)

(1:0,M)

(1:M)

(M:M)

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Relational Model Data

Linkages (>1 table) No explicit pointers are present. The data are viewed as a

collection of independent tables.

Relations are formed by an attribute that is common to bothtables in the relation.

Assignment of foreign keys:

if 1 to 1association, either of the tables primary key may

be the foreign key. if 1 to many association, the primary key on one of the

sides is embedded as the foreign key on the other side.

if many to many association, may embed foreign keys orcreate a separate linking table.

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Three Types of Anomalies

Insertion Anomaly: A new item cannotbe added to the table until at least oneentity uses a particular attribute item.

Deletion Anomaly: If an attribute itemused by only one entity is deleted, allinformation about that attribute item islost.

Update Anomaly: A modification on an

attribute must be made in each of therows in which the attribute appears.

Anomalies can be corrected by creatingrelational tables.

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Advantages of Relational Tables

Removes all three anomalies

Various items of interest (customers,inventory, sales) are stored in separatetables.

Space is used efficiently.

Very flexible. Users can form ad hocrelationships.

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The Normalization Process A process which systematically splits

unnormalized complex tables intosmaller tablesthat meet two conditions:

all nonkey (secondary) attributes in the table aredependent on the primary key

all nonkey attributes are independent of theother nonkey attributes

When unnormalized tables are split andreduced to third normal form, they must thenbe linked together by foreign keys.

S i N li i

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Steps in Normalization

Table with

repeating groups

First normalform 1NF

Second normalform 2NF

Third normalform 3NF

Higher normal

forms

Removerepeatinggroups

Remove

partialdependencies

Removetransitive

dependencies

Removeremaininganomalies

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Accountants and Data

Normalization Update anomalies can generate conflicting and

obsolete database values.

Insertion anomalies can result in unrecordedtransactions and incomplete audit trails.

Deletion anomalies can cause the loss of accountingrecords and the destruction of audit trails.

Accountantsshouldunderstand the datanormalization process and be able to determinewhether a database is properly normalized.

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Six Phases in Designing Relational

Databases1. Identify entities

identify the primary entities of the

organization construct a data model of theirrelationships

2. Construct a data model showing entity

associations determine the associations betweenentities

model associations into an ER diagram

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Databases3. Add primary keys and attributes

assign primary keys to all entities in the

model to uniquely identify records every attribute should appear in one or

more user views

4. Normalize and add foreign keys remove repeating groups, partial and

transitive dependencies

assign foreign keys to be able to link tables

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Databases

5. Construct the physical database

create physical tables

populate tables with data

6. Prepare the user views

normalized tables should support allrequired views of system users

user views restrict users from haveaccess to unauthorized data

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Distributed DataProcessing

Site CSite BSite A

CentralizedDatabase

Central

Site

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Distributed Data Processing

Data processing is organized aroundseveral information processing units (IPUs)

distributed throughout the organization Each IPU is placed under the control of the

end user.

DDP does not mean

decentralization IPUs are connected to one

another and coordinated

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Advantages of DDP

Cost reductions in hardware and dataentry tasks

Improved cost control responsibility

Improved user satisfaction since controlis closer to the user level

Backup of data can be improved throughthe use of multiple data storage sites

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Disadvantages of DDP

Loss of control

Mismanagement of resources

Hardware and software incompatibility

Redundant tasks and data

Consolidating incompatible tasks

Difficulty attracting qualified personnel

Lack of standards

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The data is retained in a central location.

Remote IPUs send requests for data.

Central site services the needs of theremote IPUs.

The actual processing of the data isperformed at the remote IPU.

Centralized Databases in DDP

Environment

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Data Currency

Occurs in DDP with a centralizeddatabase

During transaction processing, data willtemporarily be inconsistent as records areread and updated.

Database lockout procedures arenecessary to keep IPUs from readinginconsistent data and from writing over atransaction being written by another IPU.

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Distributed Databases: Partitioning

Splits the central database into segments that aredistributed to their primary users

Advantages: users control is increased by having data storedat local sites

transaction processing response time is improved

volume of transmitted data between IPUs isreduced

reduces the potential data loss from a disaster

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The Deadlock Phenomenon

Especially a problem withpartitioned databases

Occurs when multiple sites lock each otherout of data that they are currently using

One site needs data locked by another site.

Special software is needed to analyze andresolve conflicts.

Transactions may be terminated and restarted.

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The Deadlock Phenomenon

A,BE, F

C,D

Locked A, waiting for C

Locked C, waiting for E

Locked E, waiting for A

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Distributed Databases: Replication The duplication of the entire database for

multiple IPUs

Effective for situations with a high degreeof data sharing, but no primary user

supports read-only queries.

Data traffic between sites is reducedconsiderably.

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Concurrency Problems and

Control Issues Database concurrency is the presence of

complete and accurate data at all IPU sites.

With replicated databases, maintainingcurrent data at all locations is difficult.

Time stamping is used to serialize

transactions. Prevents and resolves conflicts created by

updating data at various IPUs

Documents

Ch09 DBMS (Revised 20071206)