Ch09 DBMS (Revised 20071206)
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Transcript of 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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Six Phases in Designing Relational
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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Six Phases in Designing Relational
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