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Principles of Information Systems
Eighth Edition
Chapter 5
Organizing Data and Information
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Principles of Information Systems, Eighth Edition 2
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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Principles of Information Systems, Eighth Edition 3
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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Principles of Information Systems, Eighth Edition 4
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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Principles of Information Systems, Eighth Edition 5
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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Principles of Information Systems, Eighth Edition 6
The Hierarchy of Data (continued)
• Record: collection of related data fields
• Table: collection of related records
• File: collection of related tables/records
• Database: 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 5.1: The Hierarchy of Data
TableTable
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Principles of Information Systems, Eighth Edition 8
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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Principles of Information Systems, Eighth Edition 9
Data Entities, Attributes, and Keys (continued)
Figure 5.2: Keys and Attributes
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Principles of Information Systems, Eighth Edition 10
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 file-
based 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 and anomalies
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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 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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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– 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” 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