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Chapter 8
Data and Knowledge
Management
Management Information Systems, Second Edition
Effy Oz
Learning Objectives
 When you finish this chapter, you will
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 Know the difference between traditional file
organization methods and the database approach.
 Know how database management systems are used
to construct databases, populate them with data,
and manipulate the data to produce information.
 Be familiar with the different database models and
the advantages and disadvantages of each model.
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Learning Objectives
 Know the most important features and operations of
a relational database.
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 Understand how databases are changing business
operations across industries and what impact they
might have on our personal lives.
 Understand the concepts of data warehousing and
data-mining and their use in business.
 Recognize the need for knowledge storage and
management and be able to give examples of the
ways knowledge is managed in organizations.
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Managing Digital Data
 The Traditional File Approach
 Disadvantages
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 Program/Data Dependency
 Data Redundancy
 Data Integrity
 Moving to Databases
 Database Management System (DBMS)
 Queries: Request data from specified fields
 Security: Giving users different views addresses
security issue
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Managing Digital Data
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Figure 8.1 The layout of a personnel file in traditional file
organization.
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Managing Digital Data
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Figure 8.2 Different information making up a student record
retained in three different sites.
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Managing Digital Data
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Figure 8.3 Data hierarchy
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Managing Digital Data
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Figure 8.4 Different database views reveal different
combinations of data
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Managing Digital Data
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Figure 8.5 Different views of one employee
database
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Managing Digital Data
 Traditional Files vs. Databases:
Pros and Cons
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 Traditional File Advantages
 Simplicity
 Efficiency
 Customization
 Database Advantages




Reduced data redundancy
Application/data independence
Better control
Flexibility
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Database Models
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Figure 8.6 Advantages and disadvantages of database models
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Database Models
 The Hierarchical Model
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 Records are related hierarchically -- each
category is a subcategory of the next level up
 Disadvantages of hierarchical databases
 To retrieve a record, a user must start at the root
and navigate the hierarchy.
 If a link is broken, the entire branch is lost.
 Requires considerable data redundancy because
child records can have only one parent
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Database Models
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Figure 8.7 A schematic diagram of a hierarchical
database (a) and a sample part of a hierarchical database
showing relationships among different records (b)
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Database Models
 The Network Model
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 Allows a record to be linked to more than
one parent
 Supports many-to-many (N:M)
relationships
 Advantage of the network model
 Reduced data redundancy
 Disadvantages of the network model
 Complicated to build and difficult to maintain
 Difficult to navigate
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Database Models
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Figure 8.8 A schematic diagram of a network database (a)
and a sample of part of a network database showing
relationships among different records (b)
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Database Models
 The Relational Model
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 Consists of tables; links among entities are
maintained with foreign keys
 Advantages of relational databases
 Same advantages of a network database without
the complications.
 Easier to conceptualize and maintain.
 Virtually all DBMSs offered for
microcomputers accommodate the relational
model.
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Database Models
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Figure 8.9 A schematic diagram of a relational database (a)
and a sample part of a relational database showing different
tables (b)
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Database Models
 Keys
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 Fields whose values identify records for
display or processing.
 Primary key
 Uniquely identifies a record
 Linking
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Database Models
 The Object-Oriented Structure
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 Affords maintenance of data along with the
applications that process them
 Entity-Relationship Diagrams
 Conceptual blueprint of a database
 Graphical representation of all entity
relationships
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Database Models
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Figure 8.10 An entity-relationship diagram
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Components of Database
Management Systems
 The Schema
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 Describes the structure of the database
 The Data Dictionary (Metadata)
 Maintains all information supplied by the
developer when constructing the schema
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Components of Database
Management Systems
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Figure 8.12 A typical data dictionary for a staff file
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Components of Database
Management Systems
 Data Definition Language (DDL)
 Used to construct the schema
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Figure 8.13 Data definition language to create a
schema in NOMAD
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Components of Database
Management Systems
 Data Manipulation Language (DML)
 Used to query the database
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Figure 8.14 A Paradox query by example
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Relational Operations
 Data Manipulation
 Select, Project, Join
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 Structured Query Language (SQL)
 International standard DDL and DML for
relational DBMS.
 Advantages of using SQL
 Users do not need to learn different DDLs and DMLs.
 SQL can be embedded in widely used 3rd generation
languages, increasing efficiency and effectiveness.
 Programmer not forced to rewrite statements since SQL
statements are portable.
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Relational Operations
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Figure 8.15 A join table of professors and their
students
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Popular Database
Management Systems
DATABASE MODEL
Hierarchical
Network
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Relational
Object-Relational
PRODUCT
Focus
IMS
Ramis
ADABAS
Image
Access
DB2
dBASE V
EDA/SQL
FoxPro
Ingres
NOMAD
Oracle
Paradox
Rbase
SQL/DS
SQL Server
Sybase
ObjectStore
Universal
Server
Illustra
VENDOR
Information Builders International
IBM
Online Software International
Software AG of North America
Hewlett-Packard
Microsoft
IBM
Borland International
Information Builders International
Microsoft
Ask Group
Must Software International
Oracle
Borland International
Microrim
IBM
Microsoft
Sybase
Object Design
Informix
HARDWARE
Mainframe/PC
Mainframe
Mainframe
Mainframe
Mainframe
PC
Mainframe
PC
PC
PC
PC
Mainframe/PC
Mainframe/PC
PC
PC
Mainframe
PC
PC
PC
PC
Informix
PC
Figure 8.16 Popular DBMSs
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Database Architecture
 Distributed Databases
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 Replication
 Full copy of the entire database is stored at all
sites
 Fragmentation
 Parts of database are stored where they are
most often accessed
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Database Architecture
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Figure 8.17 A replicated database: each computer holds a
copy of the entire database
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Database Architecture
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Figure 8.18 A fragmented database: each computer
holds only the part of the database that is most
frequently accessed by the local users
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Database Architecture
 Shared Resource and Client/Server
Systems
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 Four basic client/server models
 Applications run at a server
 Applications run on local PCs
 Applications run on both the local PCs and the
server
 Applications and key elements of the database
are split between the PCs and the server
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Database Architecture
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Figure 8.19 Shared resource and client/server
architectures
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Web Databases
 Databases on the Web
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



Catalogs
Libraries
Directories
Client lists and profiles
 When linking a database to the
Internet, consider
 Which application to use
 How to ensure Web surfers do not interfere
with database updates
 How to maintain security
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Data Warehousing
 Data warehouse
 Collection of data that supports
management decision making
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 Phases in Building a Data Warehouse
 Extraction Phase
 Cleansing Phase
 Loading Phase
 Data Mining
 Selecting, exploring, and modeling data to
discover unknown relationships
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Data Warehousing
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Figure 8.20 Data are warehoused for analysis and reporting
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Data-Mining
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Figure 8.21 Potential applications of data-mining
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Knowledge Management
 The attempt by organizations to:
 Transfer knowledge into databases
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 Filter and separate the most relevant
knowledge
 Organize knowledge in databases that either
 Allow other employees to easily access the
knowledge
 “Push” specific knowledge to employees based on
their prespecified needs
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Ethical and Societal Issues
A Too-Risky Info Highway
 Out of Hand -- Out of Control
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 DBMSs allow organizations to collect,
maintain, and sell vast amounts of private
personal data easily.
 Where is the Information Going?
 Many consumers provide information
daily without being aware of where it is
actually going.
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Ethical and Societal Issues
A Too-Risky Info Highway
 Personal Data Matched, Sliced , and Diced
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 Pieces of personal data may be matched and put
together to reveal private life in unexpected ways.
 Error Propagation
 In case of errors, it may be impossible to trace your
data to all organizations that have it.
 The Upside
 Database technology enables better and faster
services.
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