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Mgt 20600:
IT Management & Applications
Databases (cont.)
Decision Support Systems
Thursday
November 3, 2005
Reminders
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Reading
– For today
 Fundamentals text, Chapter 6, Information and
Decision Support Systems
Exam 2
– Next Thursday, November 10th
– Covers networks and databases
 Homeworks 3 and 4
 Fundamentals text chapters 3 and 4
 Strategies for Effective Data Storage and
Management online reading
 Lectures on networks and databases
– 75 points
– Same kind of mix of questions as on first exam
Review session
– Next Monday at 7pm
– Location to be announced
Extra Credit Opportunity
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Mr. Charles Phillips, President of Oracle
– Presentation on "Leadership and Innovation in
Technology“
– Broad range of topics in his presentation including:
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Innovation -- Challenges and Opportunities
Industry Trends -- Current and Future
Aggressive Acquisition and Consolidation -- Impact on the
Software Industry and on Oracle
Personal Views on Leadership
– Jordan Auditorium in the Mendoza College of Business
– Friday Nov. 4th
– 10:40 - 11:50 am (can leave at 11:45 am before Q&A)
– Two EASY extra credit questions on exam about
presentation – worth 4 points!
Traditional Approach
to Data Management
Traditional
approach: separate
data files are
created for each
application
Results in data
redundancy
(duplication)
Data
redundancy
conflicts with
data integrity
Database Approach
to Data Management
Database approach:
pool of related data is
shared by multiple
applications
Significant
advantages over
traditional
approach
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
Providing a User View
 Schema:
description of the entire
database
 User view: user-accessible portion
of the database
 Subschema
– Contains a description of a subset of the
database
– Identifies which users can view and
modify the data items in the subset
– Is used to create different user views
Providing a User View
The Use of Schemas and Subschemas
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 and the subschemas
 Data
dictionary:
a detailed description of
all the data used in the database
Creating and Modifying
the Database
A Typical Data Dictionary Entry
Storing and Retrieving Data
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
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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
– Training employees
Selecting a Database
Management System
 Important
characteristics of
databases to consider:
– Size of the database
– Number of concurrent users
– Performance
– Ability to be integrated with other
systems
– Features of the DBMS
– Vendor considerations
– Cost of the system
Object-Relational Database
Management Systems
 Object-relational
database
management system (ORDBMS)
– A DBMS capable of manipulating audio,
video, and graphical data
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 informationanalysis tool for discovering patterns
and relationships in a data
warehouse or a data mart
Data Warehouses, Data Marts,
and Data Mining
Elements of a Data Warehouse
Data Warehouse Example
Home Depot in 2002 launched a 48
terabyte IBM DB2 data warehouse
 Contains three years of sales history
 The warehouse is intended to take the
guesswork out of labor scheduling as well
as inventory planning
 Lowe's has had a Teradata warehouse with
that functionality since 2000
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Data Warehouse Example
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Premier Inc. sells access to clinical data it gathers from 400
hospitals to pharmaceutical manufacturers
Last year, the company's IBM Red Brick data warehouse
had grown to 3TB
One table included 3 billion entries
"When you go through 3 billion rows of data, you get long
runtimes," says Chris Stewart, director of data warehouse
architecture.
The problem wasn't just the size of the database, however,
but how clients used the data.
"Our users want to access all of the data from top to
bottom," says Stewart
The complex, multipass queries created by Premier's 4,000
users each week were slowing performance. Some wouldn't
run at all
Stewart brought in an all-inclusive data warehouse
appliance from Netezza Corp. in Framingham, Mass
Some calculations that took one or two days now finish in
six to eight minutes on the appliance's 108 processors
Data Mart Example
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ACNielsen's Paris offices
Customers are interested in very specific subsets
of data and specific aggregations
ACNielson has produced thousands of data marts
as part of a project called the Data Mart Factory
4TB master data warehouse that includes
regularly updated data from retailers
Runs it through a system that cranks out 3,000
client-specific data marts that ACNielsen presents
to 1,000 customers in the retailing and consumer
product manufacturing industries
Each data mart is refreshed weekly
Data Warehouses, Data Marts,
and Data Mining
Common Data-Mining Applications
Data Mining Example
Keyes' eyes were opened to the strategic
importance of IT during a trip he made in
1990 to visit 7-Eleven's licensees in Japan
 Stores customized their offerings to local
demand and by the assortment of fresh
foods they offered, from sushi to
sandwiches
 The Japanese did it with scanning data,
rudimentary data warehouses and a
nascent in-store ordering system
 When he became CEO, Keyes knew that
the U.S. stores had to do the same
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Data Mining Example
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Online retailer Overstock.com Inc. has begun connecting
users to a real-time data warehouse it completed last
month
The project's goal is to help employees gain insight into the
effectiveness of the company's online and e-mail
advertising campaigns.
Overstock is using transactional data management tools
from GoldenGate Software Inc. to pull information directly
from its business systems into the data warehouse
Now the data warehouse receives Web site clickstream data
in real time, financial and product-sales data every 15
minutes and other information hourly.
"When we launch campaigns now, we can look within five
minutes and see if they are producing lift or revenue that
would not normally have happened," Garcella said.
"You can't wait until the next day or three hours later to get
that data."
Online Analytical Processing
(OLAP)
 Software
that allows users to explore
data from a number of different
perspectives
Comparison of OLAP and Data Mining
OLAP in Depth
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One core software tool is online analytical processing
(OLAP)
Extracts, structures and stores warehoused data to enable
quick, multidimensional analysis
A dimension can be any variable your company tracks:
customer locations, sales volumes, product development
costs and so on
An OLAP data set is made up of dimensions and measures,
which can then be used for queries to elicit detailed data
breakdowns and information on associations among
variables
For example, a grill manufacturer could use an OLAP query
to correlate grill sales with weather conditions across
various locations, to determine how heat waves affect its
business in different regions.
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
 Knowledge management:
capturing a company’s collective
expertise and distributing it wherever
it can help produce the biggest
payoff
Business Intelligence Example
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Continental Airlines Inc. from worst to first.
BI that Continental gleaned from its customers helped move it
from last place in travelers' opinions nine years ago to the winner
of this year's award for best airline from London-based OAG
Worldwide Ltd.
The first move Continental made to improve frequent-flier
relations back in the mid-'90s was to consolidate 55 databases
worldwide into a single Teradata data warehouse
"We wanted one voice of the customer “
The goal was to identify high-yield customers, create loyalty
programs and get more immediate data on the cost of each flight
Flight attendants now receive information from the data
warehouse about high-value customers on a flight so they can
personally express the airline's interest in and knowledge about
the customers' recent flying experiences with Continental
The company's financial analysts can get information about the
profitability of each flight instantly after "wheels up," Cook says.
In the future, Continental wants the data warehouse to use realtime clickstream data to automatically generate targeted offers to
Continental's Web site visitors.
Business Intelligence Example
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Data warehouse cuts costs for ... cost-conscious Southwest
Airlines Co
The Dallas-based carrier centralized its BI group two years ago
around a Teradata data warehouse in order to keep a lid on IT
costs through better systems management and more efficient
staffing policies
"We're the low-cost airline, so we should have a low-cost
infrastructure"
Besides helping to hold down IT spending, the 2TB data
warehouse helps business analysts cut corporate costs
Annual savings from ideas generated through use of the data
warehouse at between $1.2 million and $1.4 million
As a result of that success, the data warehouse is destined to
grow. It will increase to 3TB by next summer and possibly double
that volume by 2007.
IT team is developing better ways of handling ad hoc query
requests from end users and creating dashboard-style tools for
the airline's executives.
Decision Making as a
Component of Problem Solving
 Decision-making
phase: first part
of problem-solving process
– Intelligence stage: potential problems
or opportunities are identified and
defined
– Design stage: alternative solutions to
the problem are developed
– Choice stage: a course of action is
selected
Decision Making as a
Component of Problem Solving
 Problem
solving: a process that
goes beyond decision making to
include the implementation stage
 Implementation stage: a solution
is put into effect
 Monitoring stage: decision makers
evaluate the implementation
Decision Making as a
Component of Problem Solving
How Decision Making Relates to Problem
Solving
Programmed Versus
Nonprogrammed Decisions
 Programmed
decisions
– Decisions made using a rule, procedure,
or quantitative method
– Easy to computerize using traditional
information systems
 Nonprogrammed
decisions
– Decision that deals with unusual or
exceptional situations
– Not easily quantifiable
Optimization, Satisficing, and
Heuristic Approaches
Optimization model: a process that
finds the best solution, usually the one
that will best help the organization meet
its goals
 Satisficing model: a process that finds a
good—but not necessarily the best—
problem solution
 Heuristics: commonly accepted
guidelines or procedures that usually find
a good solution
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Management Information
Systems in Perspective
A
management information system
(MIS) provides managers with
information that supports effective
decision making and provides
feedback on daily operations
 The use of MISs spans all levels of
management
Management Information
Systems in Perspective
Sources of Managerial Information
Inputs to a Management
Information System
 Internal
data sources
– TPSs and ERP systems and related
databases; data warehouses and data
marts; specific functional areas
throughout the firm
 External
data sources
– Customers, suppliers, competitors, and
stockholders, whose data is not already
captured by the TPS; the Internet;
extranets
Outputs of a Management
Information System
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Scheduled report: produced periodically, or on
a schedule
Key-indicator report: summary of the previous
day’s critical activities
Demand report: developed to give certain
information at someone’s request
Exception report: automatically produced when
a situation is unusual or requires management
action
Drill-down report: provides increasingly
detailed data about a situation
Functional Aspects of the MIS
 Most
organizations are structured
along functional lines or areas
 The MIS can be divided along
functional lines to produce reports
tailored to individual functions
Functional Aspects of the MIS
The MIS is an
integrated collection of
functional information
systems, each supporting
particular functional
areas.
Financial Management
Information Systems
 Financial
MIS: provides financial
information to all financial managers
within an organization
– Profit/loss and cost systems
– Auditing
– Uses and management of funds
Financial Management
Information Systems
Overview of a Financial MIS
Manufacturing Management
Information Systems
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The manufacturing MIS subsystems and
outputs monitor and control the flow of
materials, products, and services through
the organization
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Design and engineering
Production scheduling
Inventory control
MRP (material requirements planning)
Process control
Quality control
Manufacturing Management
Information Systems
Overview of a Manufacturing MIS
Marketing Management
Information Systems
 Marketing
MIS: supports
managerial activities in product
development, distribution, pricing
decisions, promotional effectiveness,
and sales forecasting
– Marketing research
– Product development
– Promotion and advertising
– Product pricing
Marketing Management
Information Systems
Overview of a Marketing MIS
Human Resource Management
Information Systems
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Human resource MIS: concerned with
activities related to employees and
potential employees of an organization
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Needs and planning assessments
Recruiting
Training and skills development
Scheduling and assignment
Employee benefits
Outplacement
Human Resource Management
Information Systems
Overview of a Human Resource MIS
Other Management Information
Systems
 Accounting
MIS: provides
aggregate information on accounts
payable, accounts receivable, payroll,
and many other applications
 Geographic information system
(GIS): capable of assembling,
storing, manipulating, and displaying
geographic information
An Overview of Decision
Support Systems
A
DSS is an organized collection of
people, procedures, software,
databases, and devices used to
support problem-specific decision
making and problem solving
 The focus of a DSS is on decisionmaking effectiveness when faced
with unstructured or semistructured
business problems
Capabilities of a Decision
Support System
 Support
all problem-solving phases
 Support different decision
frequencies
 Support different problem structures
 Support various decision-making
levels
Capabilities of a Decision
Support System (continued)
Decision-Making Level
A Comparison of DSS and MIS
Comparison of DSSs and MISs
A Comparison of DSS and MIS
(continued)
Comparison of DSSs and MISs
Components of a Decision
Support System
Conceptual Model of a DSS
Components of a Decision
Support System
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Database
External database access
Access to the Internet and corporate intranet,
networks, and other computer systems
Model base: provides decision makers access to
a variety of models and assists them in decision
making
Dialogue manager: allows decision makers to
easily access and manipulate the DSS and to use
common business terms and phrases
Group Support Systems
 Group
support system (GSS)
– Consists of most elements in a DSS,
plus software to provide effective
support in group decision making
– Also called group decision support
system or computerized collaborative
work system
Characteristics of a GSS That
Enhance Decision Making
 Special
design
 Ease of use
 Flexibility
 Decision-making support
 Anonymous input
 Reduction of negative group behavior
 Parallel communication
 Automated record keeping
GSS Software
 Often
called groupware or workgroup
software
 Helps with joint workgroup
scheduling, communication, and
management
 Examples: Lotus Notes, Microsoft’s
NetMeeting, Microsoft Exchange,
NetDocuments Enterprise, Collabra
Share, OpenMind, TeamWare
GSS Alternatives
GSS Alternatives
GSS Alternatives
The GSS Decision Room
Executive Support Systems
 Executive
support system (ESS):
specialized DSS that includes all
hardware, software, data,
procedures, and people used to
assist senior-level executives within
the organization
Executive Support Systems in
Perspective
 Tailored
to individual executives
 Easy to use
 Drill-down capable
 Support the need for external data
 Can help when uncertainty is high
 Future-oriented
 Linked to value-added processes
Capabilities of Executive
Support Systems
 Support
for defining an overall vision
 Support for strategic planning
 Support for strategic organizing and
staffing
 Support for strategic control
 Support for crisis management