Fundamentals of Information
Systems
Fourth Edition
Chapter 3
Organizing Data and Information
Principles and Learning Objectives
• Data management and modeling are key aspects
of organizing data and information
– Define general data management concepts and
terms, highlighting the advantages of the database
approach to data management
– Describe the relational database model and outline
its basic features
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Principles and Learning Objectives
(continued)
• A well-designed and well-managed database is an
extremely valuable tool in supporting decision
making
– Identify the common functions performed by all
database management systems and identify popular
user database management systems
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Principles and Learning Objectives
(continued)
• The number and types of database applications will
continue to evolve and yield real business benefits
– Identify and briefly discuss current database
applications
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Why Learn About Database Systems?
• Database systems process and organize large
amounts of data
• Examples
– Marketing manager can access customer data
– Corporate lawyer can access past cases and
opinions
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Introduction
• Database: an organized collection of data
• Database management system (DBMS): group of
programs to manage database
– Manipulates database
– Provides an interface between database and the
user of the database and other application programs
• Database administrator (DBA): skilled IS
professional who directs all activities related to an
organization’s database
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Data Management
• Without data and the ability to process it, an
organization could not successfully complete most
business activities
• Data consists of raw facts
• For data to be transformed into useful information,
it must first be organized in a meaningful way
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The Hierarchy of Data
• Bit (a binary digit): a circuit that is either on or off
• Byte: eight bits
• Character: basic building block of information
– Each byte represents a character
– Can be an uppercase letter, lowercase letter,
numeric digit, or special symbol
• Field: typically a name, number, or combination of
characters that describes an aspect of a business
object or activity
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The Hierarchy of Data (continued)
• Record: a collection of related data fields
• File: a collection of related records
• Database: a collection of integrated and related
files
• Hierarchy of data: bits, characters, fields, records,
files, and databases
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The Hierarchy of Data (continued)
Figure 3.1: The Hierarchy of Data
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Data Entities, Attributes, and Keys
• Entity: a generalized class of people, places, or
things (objects) for which data is collected, stored,
and maintained
• Attribute: characteristic of an entity
• Data item: value of an attribute
• Key: field or set of fields in a record that is used to
identify the record
• Primary key: field or set of fields that uniquely
identifies the record
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Data Entities, Attributes, and Keys
(continued)
Figure 3.2: Keys and Attributes
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The Database Approach
• Traditional approach to database management:
separate data files are created for each application
– Results in data redundancy (duplication)
– Data redundancy conflicts with data integrity
• Database approach to database management: pool
of related data is shared by multiple applications
– Significant advantages over traditional approach
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The Database Approach (continued)
Figure 3.3: The Database Approach to Data Management
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The Database Approach (continued)
Table 3.1: Advantages of the Database Approach
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The Database Approach (continued)
Table 3.1: Advantages of the Database Approach (continued)
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The Database Approach (continued)
Table 3.2: Disadvantages of the Database Approach
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Data Modeling and the Relational
Database Model
• When building a database, consider:
– Content: What data should be collected, at what
cost?
– Access: What data should be provided to which
users and when?
– Logical structure: How should data be arranged to
make sense to a given user?
– Physical organization: Where should data be
physically located?
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Data Modeling
• Building a database requires two types of designs
– Logical design
• Abstract model of how data should be structured and
arranged to meet an organization’s information needs
– Physical design
• Fine-tunes the logical database design for
performance and cost considerations
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Data Modeling (continued)
• Data model: a diagram of data entities and their
relationships
• Entity-relationship (ER) diagrams: data models
that use basic graphical symbols to show the
organization of and relationships between data
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Data Modeling (continued)
Figure 3.4: An Entity-Relationship (ER) Diagram for a Customer Order
Database
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The Relational Database Model
• Relational model: all data elements are placed in
two-dimensional tables (relations), which are the
logical equivalent of files
• In the relational model
– Each row of a table represents a data entity
– Columns of the table represent attributes
– Domain: the allowable values for data attributes
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The Relational Database Model
(continued)
Figure 3.5: A Relational Database Model
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Manipulating Data
•
•
•
•
Selecting: eliminates rows according to criteria
Projecting: eliminates columns in a table
Joining: combines two or more tables
Linking: relates or links two or more tables using
common data attributes
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Manipulating Data (continued)
Figure 3.6: A Simplified ER Diagram Showing the Relationship Between
the Manager, Department, and Project Tables
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Manipulating Data (continued)
Figure 3.7: Linking Data Tables to Answer an Inquiry
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Database Management Systems
(DBMS)
• Interface between:
– Database and application programs
– Database and the user
• Creating and implementing the right database
system ensures that the database will support both
business activities and goals
• DBMS: a group of programs used as an interface
between a database and application programs or a
database and the user
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Overview of Database Types
• Flat file
– Simple database program whose records have no
relationship to one another
• Single user
– Only one person can use the database at a time
– Examples: Access, FileMaker, and InfoPath
• Multiple user
– Allows dozens or hundreds of people to access the
same database system at the same time
– Examples: Oracle, Sybase, and IBM
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Providing a User View
• Schema: description of the entire database
• Large database systems typically use schemas to
define the tables and other database features
associated with a person or user
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Creating and Modifying the Database
• Data definition language (DDL)
– Collection of instructions/commands that define and
describe data and data relationships in a database
– Allows database creator to describe the data and the
data relationships that are to be contained in the
schema
• Data dictionary: a detailed description of all the
data used in the database
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Creating and Modifying the Database
(continued)
Figure 3.10: Using a Data Definition Language to Define a Schema
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Creating and Modifying the Database
(continued)
Figure 3.11: A Typical Data Dictionary Entry
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Storing and Retrieving Data
• When an application requests data from the DBMS,
the application follows a logical access path
• When the DBMS goes to a storage device to
retrieve the requested data, it follows a path to the
physical location (physical access path) where the
data is stored
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Storing and Retrieving Data
(continued)
Figure 3.12: Logical and Physical Access Paths
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Manipulating Data and Generating
Reports
• Query-By-Example (QBE): a visual approach to
developing database queries or requests
• Data manipulation language (DML): commands
that manipulate the data in a database
• Structured Query Language (SQL): ANSI
standard query language for relational databases
• Database programs can produce reports,
documents, and other outputs
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Manipulating Data and Generating
Reports (continued)
Table 3.3: Examples of SQL Commands
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Database Administration
• Database administrator (DBA): directs or performs
all activities to maintain a database environment
– Designing, implementing, and maintaining the
database system and the DBMS
– Establishing policies and procedures
– Employee training
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Popular Database Management
Systems
• Popular DBMSs for end users: Microsoft Access
and FileMaker Pro
• Entire market includes databases by IBM, Oracle,
and Microsoft
• Examples of open-source database systems:
PostgreSQL and MySQL
• Many traditional database programs are now
available on open-source operating systems
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Special-Purpose Database Systems
• Specialized database packages are used for
specific purposes or in specific industries
– Israeli Holocaust Database
– Hazmat database
– Art and Antique Organizer Deluxe
• Special-purpose database by Tableau can be used
to store and process visual images
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Selecting a Database Management
System
• Important characteristics of databases to consider
–
–
–
–
–
–
Size of the database
Cost of the system
Number of concurrent users
Performance
Ability to be integrated with other systems
Vendor considerations
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Using Databases with Other Software
• Database management systems are often used
with other software packages or the Internet
• A database management system can act as a
front-end application or a back-end application
– Front-end application: interacts with users
– Back-end application: interacts with applications
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Database Applications
• Database applications manipulate content of a
database to produce useful information
• Common manipulations are searching, filtering,
synthesizing, and assimilating the data
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Linking Databases to the Internet
• Linking databases to the Internet is important for
many organizations and people
• Semantic Web
– Developing a seamless integration of traditional
databases with the Internet
– Allows people to access and manipulate a number of
traditional databases at the same time through the
Internet
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Data Warehouses, Data Marts, and
Data Mining
• Data warehouse: collects business information
from many sources in the enterprise
• Data mart: a subset of a data warehouse
• Data mining: an information-analysis tool for
discovering patterns and relationships in a data
warehouse or a data mart
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Data Warehouses, Data Marts, and
Data Mining (continued)
Figure 3.17: Elements of a Data Warehouse
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Data Warehouses, Data Marts, and
Data Mining (continued)
Table 3.5: Common Data-Mining Applications
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Business Intelligence
• Business intelligence (BI): gathering the right
information in a timely manner and usable form and
analyzing it to have a positive impact on business
– Turns data into useful information that is then
distributed throughout an enterprise
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Business Intelligence (continued)
• Competitive intelligence: aspect of business
intelligence limited to information about competitors
and the ways that knowledge affects strategy,
tactics, and operations
• Counterintelligence: steps an organization takes
to protect information sought by “hostile”
intelligence gatherers
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Distributed Databases
• Distributed database
– Data may be spread across several smaller
databases connected via telecommunications
devices
– Corporations get more flexibility in how databases
are organized and used
• Replicated database
– Holds a duplicate set of frequently used data
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Online Analytical Processing (OLAP)
• Software that allows users to explore data from a
number of different perspectives
Table 3.6: Comparison of OLAP and Data Mining
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Object-Oriented and Object-Relational
Database Management Systems
• Object-oriented database
– Stores both data and its processing instructions
– Method: a procedure or action
– Message: a request to execute or run a method
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Object-Oriented and Object-Relational
Database Management Systems
(continued)
• Object-oriented database management system
(OODBMS)
– Programs that manipulate an object-oriented
database and provide a user interface and
connections to other application programs
• Object-relational database management system
(ORDBMS)
– A DBMS capable of manipulating audio, video, and
graphical data
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Visual, Audio, and Other Database
Systems
• Visual databases for storing images
• Audio databases for storing sound
• Virtual database systems: allow different
databases to work together as a unified database
system
• Other special-purpose database systems
– Spatial data technology: stores and accesses data
according to the locations it describes and permits
spatial queries and analysis
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Summary
• Hierarchy of data: bits, characters, fields, records,
files, and databases
• Entity: generalized class of people, places, or things
(objects) for which data is collected, stored, and
maintained
• Attribute: characteristic of an entity
• Data model: diagram of data entities and
relationships
• Relational model: describes data in which all
elements are placed in two-dimensional tables
called relations
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Summary (continued)
• Selecting: eliminates rows according to criteria
• Projecting: eliminates columns in a table
• A database management system (DBMS) is a
group of programs used as an interface between:
– Database and application programs
– Database and the user
• Data dictionary: detailed description of all the data
used in the database
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Summary (continued)
• Data warehouse: database that collects business
information from all aspects of a company’s
processes, products, and customers
• Data mining: an information-analysis tool for
discovering patterns and relationships in a data
warehouse
• Object-oriented database: stores both data and its
processing instructions
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