Transcript Slide 1

Chapter 12
SYSTEM DEVELOPMENT
AND ACQUISITION
Learning Objectives
• Understand the basic concepts of systems
development
• Discuss the major steps in developing a decision
support system (DSS) and management support
system (MSS) application
• Describe the major MSS applications and list their
major functionalities
• List the major MSS application development
options, along with their benefits and limitations
Learning Objectives
• Describe the four phases of the system development life
cycle: planning, analysis, development, and
implementation (PADI)
• Understand prototyping and throwaway prototyping and
why MSS are typically developed using these methods
• Discuss various MSS application outsourcing options,
including the use of an application service provider (ASP)
and utility computing
Learning Objectives
• Describe some major MSS software packages and MSS
application suites
• Describe various methods for connecting an MSS
application to back-end systems and databases
• Discuss the value and technical foundation of Web
services in integrated applications
• Understand the service-oriented architecture (SOA) and
its relationship to MSS
Learning Objectives
• Describe the criteria used in selecting an outsourcing
vendor and package
• Describe the factors that lead to MSS success or failure
• Discuss the importance of project management and the
skills a good project manager needs to have
• Understand the learning process that occurs during MSS
development
What Types of Support Systems
Should You Build?
• Introduction to MSS development
– Types of Support Systems
• Infrastructure
– Data warehouses and business intelligence systems
– Knowledge management systems
– Enterprise information systems
– Portals
The gateways to Web sites; they can be public (like
Yahoo!), or private (corporate portals)
What Types of Support Systems
Should You Build?
• Introduction to MSS development
– Types of Support Systems
• Specific applications
• Tools and tool kits
• Platforms
The Landscape and Framework
of MSS Application Development
The Landscape and Framework
of MSS Application Development
• Step 1: Planning, identifying, and justifying MSS
• Step 2: Creating an MSS architecture
– MSS architecture
A plan for organizing the underlying infrastructure and applications of
the MSS project
The Landscape and Framework
of MSS Application Development
• Step 3: Selecting a development option
– Build the system in house
– Have a vendor build a custom-made system
– Buy an existing application and install it, with or without
modifications, by yourself or through a vendor
– Lease standard software from an ASP, utility computing,
or set up a software-as-a-service arrangement
– Enter into a partnership or an alliance that will enable
the company to use someone else's application
– Use a combination of these approaches
The Landscape and Framework
of MSS Application Development
• Step 4: Installing, testing, connecting, and deploying MSS
applications
• Step 5: Operations, maintenance, and updating
The Landscape and Framework
of MSS Application Development
• Managing the development process
– The development process can be fairly complex and must be
managed properly
– For medium to large applications, a project team is usually created
to manage the process and the vendors
• Project management software
Development Options
for MSS Applications
• In-house development: Insourcing
– Development options for in-house development
• Building from scratch
• Building from components
• Integrating applications
DSS Development Issues
• DSS must usually be custom tailored
– The application are diverse, ranging from data-oriented DSS
to model-oriented DSS in different functional areas
– The vendors assisted in the DSS Construction
– Hardware, networking, man-machine interface and potential
impact of DSS on the individual and groups. Software
problem focused in this chapter
– Other problem are:
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DSS Development Issues
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System development life cycle (SDLC)
Prototyping
Objective-Oriented Developing Method
ROMC
Organizing and forming the development team
Complex process
Technical issues
Behavioral issues
Different approaches
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DSS Development Platform
• General-purpose programming language, such as COBOL or
PASCAL. Little has been used in 1990s
• Fourth-generation language (4GL), like a SQL.
• OLAP with a data warehouse or large database
• DSS integrated development tool (generator, engine), such as
Excel, Lotus Domino.
• Domain-specific DSS generator, such SAS, MAPLE, now
Mathmatica, Matlab.
• Use the CASE methodology
• Integrate several of the above
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Traditional Systems Development Life
Cycle (SDLC) (Waterfall)
Need
Planning
Analysis
Design
Implementation
System
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Traditional Systems Development Life
Cycle (SDLC)
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Phase A-Planning,
Phase B-Research,
Phase C-System Analysis and Conceptual Design,
Phase D-Design,
Phase E-Construction,
Phase F-Implementation,
Phase G-Maintenance and Documentation,
Phase H-Adaptation
• Simplifying Into Four Phases:
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Planning (Phase A, and Phase B) or initiation
Analysis (Phase C)
Design (Phase C , D, and E)
Implementation (Phase F, G, and H)
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Traditional Systems Development Life
Cycle (SDLC)
• Planning - Why Build the System?
Minor Step
Deliverable
1. Identify business value
2. Analyze feasibility
3. Develop work plan
4. Staff project
System request
Feasibility study
Work plan
Staffing plan,
Project charter
Project management tools
CASE tool
Standards list
Project binders / files
Risk assessment
5. Control and direct project
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Traditional Systems Development Life
Cycle (SDLC)
• Analysis- Who, What, When, Where?
Minor Step
Deliverable
6. Analyze problem
Analysis plan
7. Gather information
Information
8. Model process(es)
Process model
9. Model data
Data model
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Traditional Systems Development Life
Cycle (SDLC)
• Design - How Will the System Work?
Minor Step
Deliverable
10. Design physical system
Design plan
11. Design architecture
Architecture design,
Infrastructure design
12. Design interface
Interface design
13. Design database and files
Data storage design
14. Design program(s)
Program design
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Traditional Systems Development Life
Cycle (SDLC)
• Implementation--- System Delivery
Minor Step
Deliverable
15. Construction
Test plan,
Programs,
Documentation
16. Installation
Conversion plan,
Training plan
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Traditional Systems Development Life
Cycle (SDLC)
• Common Implementation Headaches
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No project team or management support
Hazy purpose; no defined schedule; ballooning scope
Unclear aspects of make vs. buy decisions
Few project integrations are functional out of the box
Qualitative benefits
No user buy in
Poor project management skills
No accountability (责任) / no responsibility
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Traditional Systems Development Life
Cycle (SDLC)
• CASE Tools Functions
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Information systems for systems analysts
Can help manage system development
Upper CASE (assists in analysis)
Lower CASE (manages diagrams and code generation)
Integrated CASE (both)
• Often used tools:
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Oracle Enterprise Development Suite
Rational Rose
Paradigm Plus
Visible Analyst
Logic Works Suite
AxiomSys and AxiomDsn
V32 & X32
Visual Studio
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Traditional Systems Development Life
Cycle (SDLC)
• Project Management (PM)
– Team leader must have good PM skills
– Major reason for IS development failures-bad PM skills
– Only 26% of all projects surveyed (23,000) in 1998 succeeded
– 28% failed, 46% challenged
– Lower success rates for large companies
– Better PM skills needed
• Skills for Project Managers
– Technology and business knowledge
– Judgment
– Negotiation
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Traditional Systems Development Life
Cycle (SDLC)
– Good communication
– Organization
• Implementation Failures (DW Example)
– No user involvement
– No clear objectives stated early
– No real executive sponsorship
– Not appropriate for the DSS development
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Alternative Development
Methodologies
• Parallel development
• Rapid application development (RAD) methodologies
– Phased development
– Prototyping
– Throwaway prototyping
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Alternative Development
Methodologies
• Parallel Development
– Multiple copies of design and implementation phases
– To develop separate subsystems
– All come together in a single implementation phase
• Phased Development
– Break system up into versions developed sequentially
– Each version has more functionality
– Evolves into a final system
– Users gain functionality quickly
– But initial systems are incomplete
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Alternative Development
Methodologies
• Prototyping (also called Evolutionary Prototyping Process,
iterative process, middle-out process, adaptive design,
incremental design) Characteristics:
– Performing analysis, design, and implementation phases
concurrently, and repeatedly
– Users see system functionality quickly and provide feedback
– Decision maker learns about problem
– But can lose gains in repetition
• Aims: building a DSS in a series of short steps with immediately
feedback from users to ensure that development is proceeding
correctly.
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Alternative Development
Methodologies
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Developing processes:
– Select an important sub-problem to be built first. User and the
builder jointly identify a subproblem for which the initial DSS
is constructed. This early joint effort sets up initial working
relationships between the participants and opens the lines of
communication. The subproblem should be small enough that
the nature of the problem, the need for computer-based support,
and the nature of the at support are clear. It should have high
interest value to the decision maker even if that interest is shortlive.
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Alternative Development
Methodologies
– Develop a small but usable system for the decision maker. No
major system analysis or feasibility analysis is involved. In
fact, the builder and the user go through all the steps of the
system development process quickly, though on a small scale.
The system should, out of necessarily, be simple.
– Evaluate the system constantly. At the end of each cycle the
system is evaluated by the user and builder. Evaluation is an
integral part of the development process, and is the control
mechanism for the entire iterative design process. The
evaluation mechanism is what keeps the cost and effort of
developing a DSS
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Alternative Development
Methodologies
– consistent with its value. At the end of the evolution a decision
is made on whether to further refine the DSS, or to stop.
– Refine, expand, and modify the system in cycles. Subsequent
cycles expand and improve the original version of the DSS. All
the analysis, design, construction, implementation, and
evaluation steps are repeated in each successive refinement.
• Advantages of Prototyping
– Short developing time
– Short user reaction time
– Improve user understanding of the system, its information
needs, and its capabilities.
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Alternative Development
Methodologies
– Low cost.
• Disadvantages and Limitations
– Gains maybe lost.
• Gains includes: Understanding Information systems benefits and costs,
a detailed description of the business’s information needs, an easy to to
maintain information system design, a well-tested information system,
and well-prepared users.
– Combined with the critical success factor method
• Depend on the DSS built by the end-user or a DSS team.
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Prototyping
Need
Planning
Analysis
Design
Implementation
Prototype
Prototype Not OK
Prototype OK
System
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Alternative Development
Methodologies
• Throwaway Prototyping
– Like prototyping and SDLC
– Analysis phase is thorough
– Design prototypes assist in understanding the system
– Example: can use Excel, then Visual Basic
• Prototyping for DSS Development
– Problems are semistructured or unstructured
– Managers and developers may not completely understand problem
– Use prototyping
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Throwaway Prototyping
Need
Planning
Analysis
Design
Design
Design Prototype
Not OK
Implementation
Implementation
Design
Prototype
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Alternative Development
Methodologies
• Why Prototyping?
– Users and managers involved in every phase and iteration
– Learning is part of design
– Prototyping bypasses the information requirement definition
– Short interval between iterations
– Initial prototype must be low cost
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Team-Developed DSS
• A team-Developed DSS needs:
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Substantial effort.
Extensive planning and organization
Some generic activities
Group of people to build and to manage it
(users, intermediaries, DSS builder, technical support experts and
IS personnel)
Size depends on
• Effort
• Tools
• For example, some project needs 2-3 people, but other maybe 15-20
people.
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Team-Developed DSS
• DSS development group varies:
– Within the IS department
– As a highly placed executive staff group
– Within the finance or other functional area
– Within the industrial engineering department
– Within the management science group
– Within the information center group
• The process that a DSS team may follow depends on the specific
application. The group may be temporary, created for a specific
DSS, or it may be permanent, in which case the group members are
assigned to specific DSS project.
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Team-Developed Versus UserDeveloped DSS
• DSS 1970s and early 1980s were large-scale, complex systems designed
primarily to provide organizational support. Therefore, these process needs team
effort to complete and maintain.
•
Another approach is user-developed system.
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Personal computers
Computer communication networks
PC-mainframe communication
Friendly development software
Reduced cost of software and hardware
Increased capabilities of personal computers
Enterprise-wide computing
Easy accessibility to data and models
Client/server architecture
Now OLAP
Balance
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End-user Computing and
User-Developed DSS
• End-user Computing (end-user development): development
and use of computer-based information systems by people outside
the formal information systems areas. This definition includes
many people, such as manager, professionals using PCs, Secretaries
using Word processing tools, etc.
• End-users Can be
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At any level of the organization
In any functional area
Levels of computer skill vary
Growing
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End-user Computing and
User-Developed DSS
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End-User Developed DSS Advantages
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Short delivery time
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Eliminate extensive and formal user requirements specifications
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Reduce some DSS implementation problems
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Low cost
End-User Developed DSS Risks
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Poor Quality
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Quality Risks
 Substandard or inappropriate tools and facilities
 Development process risks
 Data management risks
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Increased Security Risks
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Problems from Lack of Documentation and Maintenance Procedures
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End-user Computing and
User-Developed DSS
• Issues in Reducing End-User Computing Risks
– Error detection
– Use of auditing techniques
– Determine the proper amount of controls
– Investigate the reasons for the errors
– Solutions
– Spreadsheet errors
• Should use same controls as normal IS
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Developer Attributes
Age
Gender
Computer Confidence
Domain Experience
Application Expertise
Development Expertise
Math anxiety
Cognitive style
Application Type
Spreadsheet
Database
Others
End-user development
Application Outcomes
Reliability
Ease of use
Maintainability
Auditability
Cost
Problem/process Char.
Problem Complexity
Time Pressure
Existence of Review
Other
Developer Approach
Ad Doc
Structured
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Developer Configuration
Singles
Pairs
3+
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Supplement of Development Method
• ROMC system analysis method: Aims Mainly:
– The decision maker requirements and
– Capabilities of the DSS.
• Concept: Representation, Operations, Memory Aids, and Control
Mechanisms
• Representation: the user interface for the users of the DSS, (the
displaying forms of the information required for the decision
making, because any decision making needs lots of the information
(such as charts, images, figures and equations))
• Operations: manipulating the various information, including
database retrieve, data sorting and calculating, plotting;
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Supplement of Development Method
of course, various of modeling calculations are also included.
• Memory Aids: mediate results need to store so that later models or
calculation to reuse. Therefore, Memory Aids design is the data
structure and database design. It stores the variety of the valuable
information and mediate results so that sequential operations to use.
For example:
– Recording internal and external data
– Storing temporal results produced by an ad hoc analysis
– Reminding the decision makers for some operations backup design
– Directory of the status of information and the set values internally
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Supplement of Development Method
• Control Mechanisms: All of above three aspects can support
various decision process and status. Control Mechanism as a
decision procedure combined uses the representation, operations and
memory aids in which it depends on the styles , skills, and
knowledge of decision maker.
There are two kinds of functions:
– Building specification of using procedures and skills, e.g., using
menu to select a manipulation, editing etc.
– Online Help
• ROMC analyzing procedure
– Identifying various activities in each decision stage
For example, intelligence, design, choice, and implement.
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Supplement of Development Method
– Identifying the supporting functions for each activity.
– Building the key components of ROMC (identify the boundaries of
the ROMC)
• System design
• Application Case (Liang, textbook- a case of buying a auto
for personal)
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Objective-Oriented Developing
Methods For DSS
• Evolution of Objective-Oriented Technology
– Simula Language for replacing Simulation Language
– Use of auditing techniques (1967)
– Ada and Midula-2 for information hiding, (70s)
– Smalltalk, Xerox PARC, 1980
– C++, AT and T, 1981
– Visual Basic, Power Builder, Delphi etc. since 1994
– Java, C#, etc. 2000s
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Objective-Oriented Developing
Methods For DSS
• Main Concept of Objective-Oriented Technology
– To analyze and resolve the problems, the initial views of the
OOT is according to human being recognizing objective
world and thinking ways
– Objective world consists of many concrete things or events,
abstract concept, planning etc.
– Therefore, to study the problem of objective world, we can
abstract them as objects. In OOT, the objects are basic
elements. It is a core of analyzing problem.
– What is Object?
• Is of independent operations and behaviors program.
• Object vs. procedure.
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Objective-Oriented Developing
Methods For DSS
• What is Object?
– Actions executed by messages transferred between objects.
– Each object possesses itself data structure and style for storing data
– Each object possesses independent interface for accessing by other objects
Object 1
Object 2
Object 4
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User demand
Object 3
Object 5
Object 6
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Objective-Oriented Developing
Methods For DSS
• Object Class
– If a object having same structure, operation, and following
same constraint rules
– A class include: (1) name, (2) external interface, (3) internal
presentation and (4) realization.
– Characteristics:
– Class Specification---interface
– Realization--- each function how to do
– Hierarchy (Lattice)---farther class, sub-class, sub-sub-class etc.
» High level: generalization and commonality
» Low level: specials and details
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Objective-Oriented Developing
Methods For DSS
• Characteristics of Objective-Oriented Technology
– Abstraction: Any thing can be presented, structured and
unstructured. For example, table, chair, graph, sound, rule,
concept etc. But similar things will be abstracted into same class
for their similar operations, structures, and limits)
– Encapsulation: structure and procedure encapsulated into one
whole class. This can be used for data hiding. Data in a class
only can be accessed by its (this class) internal functions or data.
– Inheritance: subclass can inherit partial or whole properties of
its mother class. The subclass can extend some special
properties that the mother class don’t have.
– Polymorphism: one function can be used by different
arguments.
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UML Technology for DSS
• Resources: Universal Modeling Language
– UML origins Booch Method91, 93; OMT-1 and –2 and OOSE
(use case)
– 1994, Rational Software Corporation, combining Booch, OMT
and OOSE into UML.
• Concept of UML
– Core view: 4+1;
• 4: Logical + Implementation + Process + Deployment
• 1: Use Case
• Figure presents with
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UML Technology for DSS
Programmers
Software
Management
End Users
Functionality
Logical
View
Analysts/Testers
Behavior
Process
View
System Integrators
Performance,
Scalability, Throughput
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Implementation
View
Use
Case
View
Deployment
View
System Engineering
System Topology, Delivery
Installation, Communication
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UML Technology for DSS
• 9 standard Diagrams
– Static Views
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Use Case Diagram
Class Diagram
Object Diagram
Component Diagram
Deployment Diagram
– Dynamic Views
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Sequence Diagram
Collaboration Diagram
State Chart
Activity diagram
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UML Technology for DSS
• UML module
– UML is Specifying(规范化), Visualization(可视化),
Documentation(文档化), and Constructing(结构化) software
module language, its focus is on becoming a standard modeling
language not on standard program language.
– Common metamodel(元模型) and Notation
– UML is best for:
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OOT development
Component-based development
Higher Visualization Requirement
Components Reuse
Assisting Evaluation, statistical operating flows
Easy implementation
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Developing DSS: Putting the System
Together
• Development tools and generators
– Use of highly automated tools
– Use of prefabricated pieces
– Both increase the developer’s productivity
• DSS Development System Includes
– Request (query) handler
– System analysis and design facility
– Dialog management system
– Report generator
– Graphics generator
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Developing DSS: Putting the System
Together
– Source code manager
– Model base management system
– Knowledge-base (management) system
– Object-oriented tools
– Standard statistical and management science tools
– Special modeling tools
– Programming languages
– Document imaging tools
• DSS Development System Components
– Some may be integrated into a DSS generator
– Others may be added as needed
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Developing DSS: Putting the System
Together
– Components used to build a new DSS
– Core of system includes development language or DSS
generator
– Construction by combining programming modules
– Windows environment handles the interface
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Hardware & Software Selection
• Hardware Selection
– PCs
– Unix workstations
– Network of Unix workstations
– Web servers
– Mainframes
– Typically use existing hardware
• Software Selection (Complex because)
– At start, information requirements, etc. are unknown
– Hundreds of packages
– Software updated rapidly
– Price changes
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Hardware & Software Selection
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Many people involved in decision
Language capability problems
Different tools might be needed
Many criteria
Technical, functional, end-user, and managerial issues
Inaccurate published software reviews
Might prefer a single vendor
• Maybe use the AHP!!!
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DSS Technology Levels and Tools
• Three Levels of DSS Technology
– Specific DSS [the application]
– DSS integrated tools (generators) [Excel]
– DSS primary tools [programming languages]
• Plus
– DSS integrated tools
• Now all with Web hooks and easy GUI interfaces
• Relationships among the three levels (Figure 6.5)
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DSS Technology Levels and Tools
Specific DSS
DSS Generators
(Spreadsheets, …)
DSS Tools (Languages, …)
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DSS Research Directions and
The DSS of the Future
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More AI
Faster, more powerful computers
The Web - interfaces and DB and model access
More and better GSS
ERM/ERP
Knowledge management
Better GUI
Better telecommunications
More research on theories
More research on methods
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Putting Together an MSS
• MSS implementation issues
– Managers are more readily accepting MSS tools,
techniques, and methods
– AI tools and methods are being embedded in MSS and in
enterprise applications
– Web technologies continue to enable new developments
in MSS/BI
– GSS continue to proliferate through collaborative
computing
– Computer technology continues its fast-paced evolution
– Capabilities are increasing and costs are decreasing
– ERM/ERP systems, although extremely expensive, are
proliferating
Assignments (individual)
• Interpreting following concepts:
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SDLC
Prototyping
DSS teams or End-user Development
OODM
UML technology
ROMC
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