MANAGING INFORMATION TECHNOLOGY

levelsordData Management

Nov 20, 2013 (3 years and 8 months ago)

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Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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1

MANAGING INFORMATION TECHNOLOGY

7
th

EDITION

CHAPTER 6

MANAGERIAL SUPPORT SYSTEMS


Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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PART II
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APPLICATION AREAS

Inter
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organizational
systems:


e
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Business applications (Ch. 7)

-

B2C


link businesses with end consumers

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B2B


link businesses with other businesses

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Intermediaries

Intra
-
organizational
systems:


Enterprise systems: (Ch. 5)


support all or most of the organization


Managerial Support systems (Ch. 6)



support a specific manager or group of managers




Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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MANAGERIAL SUPPORT SYSTEMS


Decision Support Systems


Data Mining


Group Support Systems


Geographic Information Systems


Executive Information Systems


Business Intelligence Systems


Knowledge Management Systems


Expert Systems


Neural Networks


Virtual Reality

Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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DECISION SUPPORT SYSTEMS


Interactive decision support for complete or poorly structured
problems



Data often comes from transaction processing systems or data
warehouse



Incorporates data and models

Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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DECISION SUPPORT SYSTEMS


Three major components:


1.
Data management
: select
and handle appropriate data


2.
Model management
: apply
the appropriate model


3.
Dialog management
:
facilitate user interface to the
DSS

Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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DECISION SUPPORT SYSTEMS


Specific DSS


actual DSS applications that directly assist
in decision making



DSS generator


a software package (ex. Spreadsheet)
used to build a specific DSS quickly and easily

DSS Generator

DSS Model 1

DSS Model 2

DSS Model 3

used to create

Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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DATA MINING


Employs different technologies to search for (mine) “nuggets” of
information from data stored in a data warehouse



Decision techniques
:


Decision trees


Linear and logistic regression


Association rules for finding patterns


Clustering for market segmentation


Rule induction


Statistical extraction of if
-
then rules


Nearest neighbor


Genetic algorithms



Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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ONLINE ANALYTICAL PROCESSING (OLAP)


Human
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driven analysis:


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Querying against a database


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Program extracts data from the database and structures it by
individual dimensions, such as region or dealer

Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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USES OF DATA MINING

Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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DATA MINING PRODUCT EXAMPLES


Xerox installed
Rapid Insight Analytics software

to mine customer order,
sales prospects and supply chain data to develop monthly and quarterly
forecasts.



Farmers Insurance Group uses
IBM’s DecisionEdge software
to mine
data.



Vermont County store (VCS) a catalog retailer uses
SAS’s Enterprise
miner software

to segment its customers to create appropriate direct
marketing lists.



Data Mining software:


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Oracle 10g Data Mining


-

SAS Enterprise Miner


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IBM Intelligent Miner Modeling


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Angoss

Software’s Knowledge SEEKER,



Knowledge STUDIO, and Strategy BUILDER




SAS Enterprise Miner

XL Miner




Copyright © 2011 Pearson Education, Inc. publishing as Prentice Hall

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DATA MINING

More Data Mining examples


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-

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Venusian

Volcanoes