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-A system for decision making
         and problem solving.
What is DSS?
 A DSS is a computer-based information system that
  supports business or organizational decision-making
  activities.
 A DSS is a collection of integrated software
  applications and hardware that form the backbone of
  an organization’s decision making process and help to
  make decisions, which may be rapidly changing and
  not easily specified in advance.
Decision Making as a Component of
Problem Solving
                    Intelligence

        Decision
        making         Design


                                    Problem
                       Choice       solving


                   Implementation


                     Monitoring
Taxonomies
Haettenschwiler’s classification according to Relationship
  with User:-
 Passive DSS : A passive DSS is a system that aids the process
  of decision making, but that cannot bring out explicit
  decision suggestions or solutions.
 Active DSS : An active DSS can bring out such decision
  suggestions or solutions.
 Cooperative DSS : A cooperative DSS allows the decision
  maker to modify, complete, or refine the decision suggestions
  provided by the system, before sending them back to the
  system for validation.
Taxonomies(cont.)
According to Daniel Power:-
 Communication-driven DSS : It supports more than one
  person working on a shared task; examples include integrated
  tools like Microsoft's NetMeeting.
 Data-driven DSS : It emphasizes access to and manipulation of
  a time series of internal company data and, sometimes, external
  data.
 Document-driven DSS : It manages, retrieves, and manipulates
  unstructured information in a variety of electronic formats.
 Knowledge-driven DSS : It provides specialized problem-
  solving expertise stored as facts, rules, procedures, or in similar
  structures.
 Model-driven DSS : It emphasizes access to and manipulation of
  a statistical, financial, optimization, or simulation model. Model-
  driven DSS use data and parameters provided by users to assist
  decision makers in analyzing a situation; they are not necessarily
  data-intensive.
Taxonomies(cont.)

Daniel Power again differentiated it in two
ways in the basis of scope:-
 Enterprise-wide DSS : An enterprise-wide DSS is
  linked to large data warehouses and serves many
  managers in the company.
 Desktop DSS : A desktop, single-user DSS is a small
  system that runs on an individual manager's PC.
DSS Characteristics :
 Facilitation : DSS facilitate and support specific decision-
    making activities and/or decision processes.
   Interaction : DSS are computer-based systems designed for
    interactive use by decision makers or staff users who control
    the sequence of interaction and the operations performed.
   Ancillary : DSS can support decision makers at any level in
    an organization. They are NOT intended to replace decision
    makers.
   Repeated Use : DSS are intended for repeated use. A
    specific DSS may be used routinely or used as needed for ad
    hoc decision support tasks.
   Identifiable : DSS may be independent systems that collect
    or replicate data from other information systems OR
    subsystems of a larger, more integrated information system.
DSS Characteristics (cont.):
 Task-oriented : DSS provide specific capabilities that support
  one or more tasks related to decision-making, including:
  intelligence and data analysis; identification and design of
  alternatives; choice among alternatives; and decision
  implementation.
 Decision Impact : DSS are intended to improve the accuracy,
  timeliness, quality and overall effectiveness of a specific decision
  or a set of related decisions.
 Supports individual and group decision making : It provides a
  single platform that allows all users to access the same
  information and access the same version of truth, while providing
  autonomy to individual users and development groups to design
  reporting content locally.
 Comprehensive Data Access : It allows users to access data from
  different sources concurrently, leaving organizations the freedom
  to choose the data warehouse that best suits their unique
  requirements and preferences.
DSS Characteristics (cont.):
 Easy to Develop and Deploy : DSS delivers an interactive,
  scalable platform for rapidly developing and deploying
  projects. Multiple projects can be created within a single
  shared metadata. Within each project, development teams
  create a wide variety of re-usable metadata objects.
 Integrated software : DSS’s integrated platform enables
  administrators and IT professionals to develop data models,
  perform sophisticated analysis, generate analytical reports,
  and deliver these reports to end users via different channels
  (Web, email, file, print and mobile devices).
 Flexibility : DSS features are flexible and can be altered
  according to need providing a helping hand in the work
  process.
DSS Objectives :
1. Increase the effectiveness of the manager's decision-
   making process.
2. Supports the manager in the decision-making process
   but does not replace it.
3. Improve the directors effectiveness of decision
   making.
DSS Components :
DSS components may be classified as:
 Inputs : Factors, numbers, and characteristics to
  analyze.
 User Knowledge and Expertise : Inputs requiring
  manual analysis by the user.
 Outputs : Transformed data from which DSS
  "decisions" are generated.
 Decisions : Results generated by the DSS based on
  user criteria.
DSS Requirements :
 Data collection from multiple sources (sales data,
  inventory data, supplier data, market research data.
  etc.).
 Data formatting and collation.
 A suitable database location and format built for
  decision support -based reporting and analysis .
 Robust tools and applications to report, monitor, and
  analyze the data.
DSS Advantages :
1.   Time savings
2.   Enhance effectiveness
3.   Improve interpersonal communication
4.   Competitive advantage
5.   Cost reduction
6.   Increase decision maker satisfaction
7.   Promote learning
8.   Improves personal efficiency
DSS Disadvantages :
1.   Monetary cost.
2.   Overemphasize decision making.
3.   Assumption of relevance.
4.   Transfer of power.
5.   Unanticipated effects.
6.   Obscuring responsibility.
7.   False belief in objectivity.
8.   Status reduction.
9.   Information overload.
DSS Applications :
 Medical diagnosis.
 Business and Management.
 Agricultural production.
 Forest management.
Presented By :-
           SAYANTAN SUR
          BCA(H) – 2ND SEM

            THANK YOU

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Decision Support System(DSS)

  • 1. -A system for decision making and problem solving.
  • 2. What is DSS?  A DSS is a computer-based information system that supports business or organizational decision-making activities.  A DSS is a collection of integrated software applications and hardware that form the backbone of an organization’s decision making process and help to make decisions, which may be rapidly changing and not easily specified in advance.
  • 3. Decision Making as a Component of Problem Solving Intelligence Decision making Design Problem Choice solving Implementation Monitoring
  • 4. Taxonomies Haettenschwiler’s classification according to Relationship with User:-  Passive DSS : A passive DSS is a system that aids the process of decision making, but that cannot bring out explicit decision suggestions or solutions.  Active DSS : An active DSS can bring out such decision suggestions or solutions.  Cooperative DSS : A cooperative DSS allows the decision maker to modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation.
  • 5. Taxonomies(cont.) According to Daniel Power:-  Communication-driven DSS : It supports more than one person working on a shared task; examples include integrated tools like Microsoft's NetMeeting.  Data-driven DSS : It emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.  Document-driven DSS : It manages, retrieves, and manipulates unstructured information in a variety of electronic formats.  Knowledge-driven DSS : It provides specialized problem- solving expertise stored as facts, rules, procedures, or in similar structures.  Model-driven DSS : It emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model- driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data-intensive.
  • 6. Taxonomies(cont.) Daniel Power again differentiated it in two ways in the basis of scope:-  Enterprise-wide DSS : An enterprise-wide DSS is linked to large data warehouses and serves many managers in the company.  Desktop DSS : A desktop, single-user DSS is a small system that runs on an individual manager's PC.
  • 7. DSS Characteristics :  Facilitation : DSS facilitate and support specific decision- making activities and/or decision processes.  Interaction : DSS are computer-based systems designed for interactive use by decision makers or staff users who control the sequence of interaction and the operations performed.  Ancillary : DSS can support decision makers at any level in an organization. They are NOT intended to replace decision makers.  Repeated Use : DSS are intended for repeated use. A specific DSS may be used routinely or used as needed for ad hoc decision support tasks.  Identifiable : DSS may be independent systems that collect or replicate data from other information systems OR subsystems of a larger, more integrated information system.
  • 8. DSS Characteristics (cont.):  Task-oriented : DSS provide specific capabilities that support one or more tasks related to decision-making, including: intelligence and data analysis; identification and design of alternatives; choice among alternatives; and decision implementation.  Decision Impact : DSS are intended to improve the accuracy, timeliness, quality and overall effectiveness of a specific decision or a set of related decisions.  Supports individual and group decision making : It provides a single platform that allows all users to access the same information and access the same version of truth, while providing autonomy to individual users and development groups to design reporting content locally.  Comprehensive Data Access : It allows users to access data from different sources concurrently, leaving organizations the freedom to choose the data warehouse that best suits their unique requirements and preferences.
  • 9. DSS Characteristics (cont.):  Easy to Develop and Deploy : DSS delivers an interactive, scalable platform for rapidly developing and deploying projects. Multiple projects can be created within a single shared metadata. Within each project, development teams create a wide variety of re-usable metadata objects.  Integrated software : DSS’s integrated platform enables administrators and IT professionals to develop data models, perform sophisticated analysis, generate analytical reports, and deliver these reports to end users via different channels (Web, email, file, print and mobile devices).  Flexibility : DSS features are flexible and can be altered according to need providing a helping hand in the work process.
  • 10. DSS Objectives : 1. Increase the effectiveness of the manager's decision- making process. 2. Supports the manager in the decision-making process but does not replace it. 3. Improve the directors effectiveness of decision making.
  • 11. DSS Components : DSS components may be classified as:  Inputs : Factors, numbers, and characteristics to analyze.  User Knowledge and Expertise : Inputs requiring manual analysis by the user.  Outputs : Transformed data from which DSS "decisions" are generated.  Decisions : Results generated by the DSS based on user criteria.
  • 12. DSS Requirements :  Data collection from multiple sources (sales data, inventory data, supplier data, market research data. etc.).  Data formatting and collation.  A suitable database location and format built for decision support -based reporting and analysis .  Robust tools and applications to report, monitor, and analyze the data.
  • 13. DSS Advantages : 1. Time savings 2. Enhance effectiveness 3. Improve interpersonal communication 4. Competitive advantage 5. Cost reduction 6. Increase decision maker satisfaction 7. Promote learning 8. Improves personal efficiency
  • 14. DSS Disadvantages : 1. Monetary cost. 2. Overemphasize decision making. 3. Assumption of relevance. 4. Transfer of power. 5. Unanticipated effects. 6. Obscuring responsibility. 7. False belief in objectivity. 8. Status reduction. 9. Information overload.
  • 15. DSS Applications :  Medical diagnosis.  Business and Management.  Agricultural production.  Forest management.
  • 16. Presented By :- SAYANTAN SUR BCA(H) – 2ND SEM THANK YOU