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1
Technology in Action
Chapter 11
Behind the Scenes:
Databases and Information Systems
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Chapter Topics
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Databases and their uses
Database components
Types of databases
Database management systems
Relational databases
Data warehouses and data marts
Information systems
Data mining
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What is a database?
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Non-computer databases
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Paper files in a Doctor’s office
Phone book
Dictionary
Cookbook (Multi-media!)
Baseball cards (Multi-media!)
Day Planner
Sports team sign-up sheet
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Databases
Definitions from the book:
• Collections of related data
• Easily stored, sorted, organized, and queried
• Turn data into information
-----------------------------------------------------------------------------My simplified definition:
• A collection of information organized in a manner that
allows for convenient retrieval.
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My soccer team
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Their Uniforms
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The two tables are related…
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Some DB words…
• Everything is stored in a ‘table’
• A ‘record’ is everything about the person (horizontal)
• A ‘field’ is a fact about the person (Example: The
Address field for ‘Mark’ contains the word ‘London’
• All records have the same fields, just different data
stored in those fields.
• Fields are picky about what can be stored in them (data
types)
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Life Without Databases: Lists
• Often sufficient for simple tasks
• Not appropriate for complex information
• Multiple lists lead to
– Data redundancy
– Data inconsistency
– Duplicate data
– Sorting issues
– Incomplete data
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Databases
• Collections of related data
• Easily stored, sorted, organized, and
queried
• Turn data into information
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Advantages of Using Databases
• Store and retrieve
large quantities of
information
• Enable information
sharing
• Provide data
centralization
• Promote data
integrity
• Allow for flexible
use of data
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Disadvantages of Databases
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Complex to construct
Time consuming
Expensive
Privacy concerns
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Database Terminology
• Field: A category of information,
displayed in columns
• Record: A group of related fields
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Database Terminology (cont.)
• Data type: Type of data that can be
stored in a field
Data Type
Used to Store
Example of Data Stored in the Field
Text
Alphabetic or alphanumeric data
Numeric
Computational
Numbers
Computational formulas
Mirabel
CIS110
256, 1.347, $5600
Credit hours x per-credit tuition charges
Date
Dates in standard date notation
4/15/2014
Memo
Long blocks of text
Four score and seven years ago our
fathers brought forth on this continent a
new nation, conceived in liberty, and
dedicated to the proposition that all men
are created equal.
Object
Hyperlink
Multimedia files or documents
MP3 file, AVI file
A hyperlink to a Web page on the www.pearsonhighered.com/techinaction
Internet
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Database Terminology (cont.)
• Field size: defines the maximum number
of characters that a field can hold.
• Set field size to the length of the data it
contains
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Database Terminology (cont.)
• Table: A group of related records
• Primary key: A field value unique to a
record
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Database Types
• Relational databases
– Organize data in tables
– Link tables to each other through their primary
keys
• Object-oriented databases
– Store data in objects
– Also store methods for processing data
– Handle unstructured data
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Database Types (cont.)
• Multidimensional databases
– Store data in multiple dimensions
– Organize data in a cube format
• Advantages
– Can easily be customized
– Process data much faster
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Database Management
Systems (DBMS)
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Application software designed to capture
and analyze data
Four main operations of a DBMS:
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Creating databases and entering data
Viewing and sorting data
Extracting data
Outputting data
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Creating Databases and
Entering Data
• Create field
names
– Identify each
type
of data
– Data
dictionary (or
database
schema)
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Creating Databases and
Entering Data (cont.)
• Create
individual
records
– Key in
– Import
– Input form
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Data Validation
• Validation
– Process of ensuring that data entered into
the database is correct (or at least
reasonable) and complete
• Validation rules
– Range checks
– Completeness checks
– Consistency checks
– Alphabetic/numeric checks
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Data Validation (cont.)
• Example of a completeness check
Required field
Error message
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Viewing and Sorting Data
• Browse
through
records
• Sort records
by field name
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Extracting or Querying Data
• Query
– A question or
inquiry
– Provides
records based
on criteria
– Structured
Query
Language
(SQL)
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Extracting or Querying Data
(cont.)
• Modern databases provide wizards to
create queries
• Simple Query Wizard creates SQL
commands behind the scenes
• SQL view: Create, modify, or view SQL
code created by the wizard
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Outputting Data
• Reports
– Viewable or (printable) electronic output
– Summary data reports
• Export data
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Relational Database Operations
• Relational
databases
organize data
into tables
• Relationships
are links
between tables
with related data
• Common field(s)
need to exist
between tables
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Types of Relationships
• One-to-one
– For each record in a table, there is only one
corresponding record in a related table
• One-to-many
– Only one instance of a record in one table;
many instances in a related table
• Many-to-many
– Records in one table related to many records
in another
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Relational Database Operations
• Normalization of data (recording data
once) reduces data redundancy
• Foreign key: The primary key of one table
is included in another to establish
relationships with that other table
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Data Storage
• Data warehouse
– Large-scale
repository of data
– Organizes all the
data related to an
organization
– Data organized
by subject
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Populating Data Warehouses
• Source data
– Internal sources
• Company databases, etc.
– External sources
• Suppliers, vendors, etc.
– Customers or Web site visitors
• Clickstream data
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Data Staging
• Three steps:
1. Extract data from source
2. Reformat the data
3. Store the data
• Software programs and procedures
created to extract the data and reformat
it for storage
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Data Marts
• Small slices of data warehouse
• Data for a single department or for use
by specific employee groups
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Data Warehouse Process
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Managing Data:
Information Systems
• Information systems
– Software-based solutions used to gather and
analyze information
• Functions performed by information
systems include
– Acquiring data
– Processing data into information
– Storing data
– Providing output options
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Information Systems Categories
• Five categories
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2.
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5.
Office support systems
Transaction-processing systems
Management information systems
Decision support systems
Enterprise resource planning (ERP) systems
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Office Support Systems (OSSs)
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Assist employees in day-to-day tasks
Improve communications
Example: Microsoft Office
Include e-mail, word-processing,
spreadsheet, database, and presentation
programs
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Transaction-Processing
Systems (TPSs)
• Keep track of
everyday business
activities
• Batch processing
• Real-time
processing
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Management Information
Systems (MISs)
• Provide timely and accurate information for
managers in making business decisions
• Detail report
– Transactions that
occur during a
period of time
• Summary report
– Consolidated
detailed data
• Exception report
– Unusual conditions
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Decision Support Systems
(DSSs)
• Help managers develop solutions for
specific problems
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Model Management Systems
• Software that assists in building
management models in DSSs
• Can be built to describe any business
situation
• Internal and external models
• Typically contain financial and statistical
analysis tools
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Knowledge-Based Systems
• Expert system: Replicates human experts
• Natural language processing (NLP)
system: Enables users to communicate
with computers using a natural spoken or
written language
• Artificial intelligence (AI): Branch of
computer science that deals with
attempting to create computers that think
like humans
• Support concept of fuzzy logic
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Enterprise Resource
Planning Systems
• Integrate multiple data sources
• Enable smooth flow of information
• Use common database to store and
integrate information
• Allow information to be used across
multiple areas of an enterprise
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Data Mining
• Process by which great amounts of data
are analyzed and investigated
• Objective is to spot patterns or trends
within the data
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Data Mining Methods
• Classification
– Define data classes
• Estimation
– Assign a value to data
• Affinity grouping or association rules
– Determine which data goes together
• Clustering
– Organize data into subgroups
• Description and visualization
– Get a clear picture of what is happening
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Chapter 11 Summary Questions
• What is a database, and why is it
beneficial to use databases?
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Chapter 11 Summary Questions
• What components make up a database?
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Chapter 11 Summary Questions
• What types of databases are there?
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Chapter 11 Summary Questions
• What do database management systems
do?
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Chapter 11 Summary Questions
• How do relational databases organize and
manipulate data?
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55
Chapter 11 Summary Questions
• What are data warehouses and data
marts, and how are they used?
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Chapter 11 Summary Questions
• What is an information system, and what
types of information systems are used in
business?
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Chapter 11 Summary Questions
• What is data mining, and how does it
work?
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mechanical, photocopying, recording, or otherwise, without the prior written
permission of the publisher. Printed in the United States of America.
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Publishing as Prentice Hall
Chapter 11
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