Chapter 5

Principles of Information Systems

Eighth Edition

Chapter 5

Organizing Data and Information

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


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


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


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


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


The Hierarchy of Data (continued)

Figure 5.1: The Hierarchy of Data

TableTable


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


Data Entities, Attributes, and Keys (continued)

Figure 5.2: Keys and Attributes


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


The Database Approach (continued)

Figure 5.3: The Database Approach to Data Management



Table 5.1: Advantages of the Database Approach



Table 5.1: Advantages of the Database Approach (continued)



Table 5.2: Disadvantages of the Database Approach


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?


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


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


Data Modeling (continued)

Figure 5.4: An Entity-Relationship (ER) Diagram for a Customer Order Database


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


The Relational Database Model (continued)

Figure 5.5: A Relational Database Model



• 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



Figure 5.6: A Simplified ER Diagram Showing the Relationship Between the Manager, Department, and Project Tables



Figure 5.7: Linking Data Tables to Answer an Inquiry



• Data cleanup: process of looking for and fixing inconsistencies to ensure that data is accurate and complete– Eliminate redundancies and anomalies


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


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


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


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


Creating and Modifying the Database (continued)

Figure 5.10: Using a Data Definition Language to Define a Schema


Creating and Modifying the Database (continued)

Figure 5.11: A Typical Data Dictionary Entry


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


Storing and Retrieving Data (continued)

Figure 5.12: Logical and Physical Access Paths


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


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


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


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


Selecting a Database Management System

• Important characteristics of databases to consider– Database size– Database cost– Concurrent users– Performance– Integration– Vendor


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


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


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


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


Data Warehouses, Data Marts, and Data Mining (continued)

Figure 5.17: Elements of a Data Warehouse


Data Warehouses, Data Marts, and Data Mining (continued)

Table 5.8: Common Data-Mining Applications


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


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


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


Online Analytical Processing (OLAP)

• Software that allows users to explore data from a number of different perspectives


Online Analytical Processing (OLAP) (continued)

Table 5.9: Comparison of OLAP and Data Mining


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


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


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

Documents

Chapter 5