Transcript chap005a

BUSI 240
Introduction to Information Systems
Tuesday & Thursday 8:05am – 9:30am
Wyant Lecture Hall
Please sign the roster on the back table.
4-1
Current Events – What’s going on?
AOL’s Bet on Another Makeover
AOL is trying to remake itself, yet again.
The new strategy in many ways resembles the old strategy: make
acquisitions to attract traffic and reverse a continuing decline in
advertising and revenue from its dial-up Internet service. In the
latest iteration of its do-over, it is paying $315 million to buy the
liberal news commentary site The Huffington Post, not long after
paying $25 million to buy TechCrunch, the Silicon Valley
technology news blog.
http://www.nytimes.com/2011/02/08/technology/08aol.html?_r=2&ref=technology
5-2
Current Events – What’s going on?
Verizon Has Already Sold 500,000 iPhones
Estimates place the number of iPhone 4s sold by Verizon Wireless
during its short-lived pre-sale at more than half a million.
function showDesc(img) { var element =
document.getElementById("videoBoxDisplayAreaText");
if(element) element.innerHTML = img.alt; };
JPMorgan analyst Phil Cusick said in a note to clients today that
it's likely 500,000 people purchased an iPhone 4 from Verizon
Wireless during the 17-hour-long pre-sale that took place on
February 3.
In order to reach this estimate, Cusick looked back at some clues
given by Verizon Wireless in the past.
http://www.informationweek.com/blog/main/archives/2011/02/verizon_has_alr.html
5-3
Quiz #2
Should have been taken by now.
5-4
Assignment #2

Select a product to evaluate:








4-5
Digital camera
Cell phone
MP3 player
Car
Computer
Follow the steps on the spreadsheet to evaluate
three models of the product
Due February 22nd
Submit assignment to eComanion’s Drop Box
Assignment #2
 Web
sites with product reviews:
 www.cnet.com
 www.consumerreports.org
 www.consumersearch.com
 www.epinions.com
 review.zdnet.com
 www.consumerreview.com
5-6
Chapter
5a
Data Resource Management
Data Concepts
Database Management
Types of Databases
McGraw-Hill/Irwin
Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.
Examples of logical data elements
5-8
Fundamental Data Concepts



5-9
Character: single alphabetic, numeric or other symbol
Field or data item: a grouping of related characters
 Represents an attribute (a characteristic or quality) of some
entity (object, person, place or event)
 Example: salary
Record: grouping of all the fields used to describe the attributes
of an entity
 Example: payroll record with name, SSN and rate of pay
Fundamental Data Concepts


5-10
File or table: a group of related records
Database: an integrated collection of logically related data
elements
Electric Utility Database
Source: Adapted from Michael V. Mannino, Database Application Development and Design
(Burr Ridge, IL: McGraw-Hill/Irwin, 2001), p. 6.
5-11
Database Structures





5-12
Hierarchical
Network
Relational
Object-oriented
Multidimensional
Hierarchical Structure
 Early
DBMS structure
 Records arranged in tree-like structure
 Relationships are one-to-many
5-13
Hierarchical Structure
5-14
Network Structure
 Used in
some mainframe DBMS packages
 Many-to-many relationships
5-15
Network Structure
5-16
Relational Structure






5-17
Most widely used structure
Data elements are viewed as being stored in tables
Row represents record
Column represents field
Can relate data in one file with data in another file if both files
share a common data element
Provide more flexibility than hierarchical databases because
they allow users to easily receive information in response to ad
hoc queries.
Relational Structure
5-18
Relational Operations
 Select:
 Create
a subset of records that meet a stated criterion
 Example, select employees who make more than
$30,000
 Join
 Combine
two or more tables temporarily
 Looks like one big table
 Project
 Create
5-19
a subset of columns in a table
Multidimensional Structure
 Variation
of relational model
 Uses multidimensional structures to organize data
 Data elements are viewed as being in cubes
 Popular for analytical databases that support Online
Analytical Processing (OLAP)
5-20
Multidimensional Model
5-21
Object-oriented Structure
 Object
consists of
 Data
values describing the attributes of an entity
 Operations that can be performed on the data
 Encapsulation:
 Combine
data and operations
 Inheritance:
 New
objects can be created by replicated some or all of
the characteristics of parent objects
5-22
Object-oriented Structure
Source: Adapted from Ivar Jacobsen, Maria Ericsson, and Ageneta Jacobsen, The Object Advantage: Business Process
Reengineering with Object Technology (New York: ACM Press, 1995), p. 65.
Copyright @ 1995, Association for Computing Machinery. By permission.
5-23
Object-oriented Structure
 Used in
Object-oriented database management
systems (OODBMS)
 Supports complex data types
 Examples,
5-24
graphic images, video clips, web pages
Evaluation of Database Structures
 Hierarchical
 Worked
for structured routine transaction processing
 Can’t handle many-to-many relationships
 Network
 More
flexible than hierarchical
 Unable to handle ad hoc requests
 Relational
 Easily
respond to ad hoc requests
 Easier to work with and maintain
 Not as efficient or quick as hierarchical or network
5-25
Database Development
 Database
 In
 Data
Administrator (DBA)
charge of enterprise database development
Definition Language (DDL)
 Develop
and specify the data contents, relationships
and structure
 These specifications are stored in data dictionary
 Data
dictionary
 Data
base catalog containing metadata
 Metadata – data about data
5-26
Database Development
5-27
Data Planning Process
 Enterprise
Model
 Defines
basic business process of the enterprise
 Defined by DBAs and designers with end users
 Data
Modeling
 Relationships
between data elements
 Entity Relationship Diagram (ERD) common tool for
modeling
5-28
Entity Relationship Diagram
5-29
Database Design Process
 Logical
design
 Schema
– overall logical view of relationships
 Subschema – logical view for specific end users
 Data models for DBMS
 Physical
 How
design
data are to be stored and accessed on storage
devices
5-30
Logical and Physical Database
Views
5-31