Transcript IS-ch05

Principles of Information
Systems
Chapter 5
Organizing Data and Information
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
• To transform data into useful information, it must
first be organized in a meaningful way
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The Hierarchy of Data
Figure 5.1: The Hierarchy of Data
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The Hierarchy of Data
• Bit (a binary digit): represents a circuit that is
either on or off
• Byte: typically made up of eight bits
• Character: a byte represents a character; the
basic building block of information
– 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: collection of related data fields
File: collection of related records
Database: collection of integrated and related files
Hierarchy of data
– Bits, characters, fields, records, files, and databases
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Data Entities, Attributes, and Keys
• Entity: generalized class of people, places, or
things (objects) for which data is collected, stored,
and maintained
• Attribute: characteristic of an entity
• Data item: specific 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 5.2: Keys and Attributes
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The Database Approach
• Traditional approach to data management:
separate data files are created and stored for each
application program
• Database approach to data management: a pool
of related data is shared by multiple application
programs
– Offers significant advantages over the traditional filebased approach
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The Database Approach (continued)
Figure 5.3: The Database Approach to Data Management
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The Database Approach (continued)
Table 5.1: Advantages of the Database Approach
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The Database Approach (continued)
Table 5.1: Advantages of the Database Approach (continued)
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The Database Approach (continued)
Table 5.2: Disadvantages of the Database Approach
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Data Modeling and the Relational
Database Model
• When building a database, an organization must
consider:
– Content: What data should be collected and at what
cost?
– Access: What data should be provided to which
users and when?
– Logical structure: How should data be arranged so
that it makes 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 the data
should be structured and arranged to meet an
organization’s information needs
– Physical design: starts from the logical database
design and fine-tunes it for performance and cost
considerations
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Data Modeling (continued)
• Data model: 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 5.4: An Entity-Relationship (ER) Diagram for a Customer Order
Database
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The Relational Database Model
• Relational model: describes data in which all data
elements are placed in two-dimensional tables,
called relations, that are the logical equivalent of
files
– Each row of a table represents a data entity
– Columns of the table represent attributes
– Domain: allowable values for data attributes
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The Relational Database Model
(continued)
Figure 5.5: A Relational Database Model
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The Relational Database Model
(continued)
• Selecting: eliminates rows according to certain
criteria
• Projecting: eliminates columns in a table
• Joining: combines two or more tables
• Linking: manipulating two or more tables that
share at least one common data attribute to
provide useful information and reports
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The Relational Database Model
(continued)
Figure 5.6: A Simplified ER Diagram Showing the Relationship Between
the Manager, Department, and Project Tables
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The Relational Database Model
(continued)
Figure 5.7: Linking Data Tables to Answer an Inquiry
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The Relational Database Model
(continued)
• Data cleanup: process of looking for and fixing
inconsistencies to ensure that data is accurate
and complete
– Eliminate redundancies (ความซ้ าซ้อน) and
anomalies (ความผิดสภาพ)
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The Relational Database Model
(continued)
Table 5.3: Fitness Center Dues
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The Relational Database Model
(continued)
Table 5.4: Fitness Center Members
Table 5.5: Dues Paid
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Database Management Systems
(DBMSs)
• 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
– Typically used by large database systems to define
tables and other database features associated with a
person or user
• A DBMS can reference a schema (แผน) to find where
to access the requested data in relation to another
piece of data
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Creating and Modifying the Database
• Data definition language (DDL): collection of
instructions and commands used to define and
describe data and relationships in a specific
database
– Allows the database’s creator to describe the data
and relationships that are to be contained in the
schema
• Data dictionary: detailed description of all the data
used in the database
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Creating and Modifying the Database
(continued)
Figure 5.10: Using a Data Definition Language to Define a Schema
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Creating and Modifying the Database
(continued)
Figure 5.11: A Typical Data Dictionary Entry
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Storing and Retrieving Data
• When an application program requests data from
the DBMS, the application program 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 5.12: Logical and Physical Access Paths
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Manipulating Data and Generating
Reports
• Data manipulation language (DML): commands
that manipulate the data in a database
• Structured Query Language (SQL)
– Adopted by the American National Standards
Institute (ANSI) as the standard query language for
relational databases
• Once a database has been set up and loaded with
data, it can produce reports, documents, and other
outputs
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Manipulating Data and Generating
Reports (continued)
Table 5.6: Examples of SQL Commands
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Database Administration
• Role of the database administrator (DBA): plan,
design, create, operate, secure, monitor, and
maintain databases
• DBA works with both users and programmers
• A data administrator is responsible for defining and
implementing consistent principles for a variety of
data issues, including setting data standards and
data definitions; a nontechnical position
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Popular Database Management
Systems
• Popular DBMSs for end users include Microsoft’s
Access and FileMaker Pro
• Complete database management software market
includes:
– Software for professional programmers
– Databases for midrange, mainframe, and
supercomputers
• 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
• Some specialized database packages are used for
specific purposes or in specific industries
– Israeli Holocaust Database (www.yadvashem.org)
– 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
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–
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Database size
Database cost
Concurrent users
Performance
Integration
Vendor
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Using Databases with Other Software
• DBMSs can act as front-end or back-end
applications
– Front-end applications interact directly with people or
users
– Back-end applications interact with other programs
or applications
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Database Applications
• Today’s database applications manipulate the
content of a database to produce useful information
• Common manipulations are searching, filtering,
synthesizing, and assimilating the data contained in
a database using a number of database
applications
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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: database that collects business
information from many sources in the enterprise,
covering all aspects of the company’s processes,
products, and customers
• Data mart: subset of a data warehouse
• Data mining: information-analysis tool that
involves the automated discovery of patterns and
relationships in a data warehouse
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Data Warehouses, Data Marts, and
Data Mining (continued)
Figure 5.17: Elements of a Data Warehouse
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Data Warehouses, Data Marts, and
Data Mining (continued)
Table 5.8: Common Data-Mining Applications
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Business Intelligence
• Business intelligence (BI): process of gathering
enough of the right information in a timely manner
and usable form and analyzing it to have a positive
impact on business strategy, tactics, or operations
– 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” (ผูม้ ุ่งร้าย)
intelligence gatherers
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Distributed Databases
• Distributed database
– Database in which the data may be spread across
several smaller databases connected via
telecommunications devices
– Gives corporations more flexibility in how databases
are organized and used
• Replicated database
– Database that 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
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Online Analytical Processing (OLAP)
(continued)
Table 5.9: Comparison of OLAP and Data Mining
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Object-Oriented and Object-Relational
Database Management Systems
• Object-oriented database:
database that stores both
data and its processing
instructions
– Method: procedure or
action
– Message: 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): group of programs that manipulate an
object-oriented database and provide a user
interface and connections to other application
programs
• Object-relational database management system
(ORDBMS): DBMS capable of manipulating audio,
video, and graphical data
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Visual, Audio, and Other Database
Systems
• Databases for storing images
• 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
• Database: a collection of integrated and related files
• Hierarchy of data: bits, characters, fields, records,
files, and databases
• Key: a field or set of fields in a record that is used to
identify the record
• Database approach to data management: a pool of
related data is shared by multiple application
programs
• Data model: diagram of entities and relationships
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Summary (continued)
• Relational model: describes data in which all
elements are placed in two-dimensional tables
called relations
• Database management system (DBMS): group of
programs used as an interface between a database
and application programs or a database and the
user
• Role of the database administrator (DBA): plan,
design, create, operate, secure, monitor, and
maintain databases
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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: information-analysis tool for the
automated discovery of patterns and relationships
in a data warehouse
• Object-oriented database: database that stores
both data and its processing instructions
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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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Review question #5
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ส วั ส ดี
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