Fundamentals of Information Systems Fourth Edition Chapter 3 Organizing Data and Information.

Fundamentals of Information Systems

Fourth Edition

Chapter 3

Organizing Data and Information

Fundamentals of Information Systems, Fourth Edition 2

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

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

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

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

• For data to be transformed into useful information, it must first be organized in a meaningful way

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

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

The Hierarchy of Data (continued)

Figure 3.1: The Hierarchy of Data

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

Data Entities, Attributes, and Keys (continued)

Figure 3.2: Keys and Attributes

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

The Database Approach (continued)

Figure 3.3: The Database Approach to Data Management

Table 3.1: Advantages of the Database Approach

Table 3.1: Advantages of the Database Approach (continued)

Table 3.2: Disadvantages of the Database Approach

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?

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

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

Data Modeling (continued)

Figure 3.4: An Entity-Relationship (ER) Diagram for a Customer Order Database

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

The Relational Database Model (continued)

Figure 3.5: A Relational Database Model

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

Manipulating Data (continued)

Figure 3.6: A Simplified ER Diagram Showing the Relationship Between the Manager, Department, and Project Tables

Manipulating Data (continued)

Figure 3.7: Linking Data Tables to Answer an Inquiry

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

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

• Large database systems typically use schemas to define the tables and other database features associated with a person or user

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

Creating and Modifying the Database (continued)

Figure 3.10: Using a Data Definition Language to Define a Schema

Creating and Modifying the Database (continued)

Figure 3.11: A Typical Data Dictionary Entry

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

Storing and Retrieving Data (continued)

Figure 3.12: Logical and Physical Access Paths

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

Manipulating Data and Generating Reports (continued)

Table 3.3: Examples of SQL Commands

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

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

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

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

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

Database Applications

• Database applications manipulate content of a database to produce useful information

• Common manipulations are searching, filtering, synthesizing, and assimilating the data

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: 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

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

Figure 3.17: Elements of a Data Warehouse

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

Table 3.5: Common Data-Mining Applications

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

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– 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

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

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

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

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

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

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

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

Fundamentals of Information Systems Fourth Edition Chapter 3 Organizing Data and Information.

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