model driven dss is a decision support system used by managers,staff members and people who interact with the business organization for analyzing semistructured and unstructured decisions.they are usually deployed as software,hardware in standalone PCs.dss basically has 4 analysis models: 1) what if analysis 2)sensitivity analysis 3)goal based analysis 4)optimized analysis
Model data driven user interacts primarily with a mathematical model and its results while data driven DSS is user interacts primarily with the data
A model-driven DSS relies on mathematical or statistical models to analyze data and make predictions, while a data-driven DSS uses historical and real-time data to generate insights and support decision-making without relying heavily on predefined models. Model-driven DSS are more structured and use algorithms to process data, while data-driven DSS focus on exploring patterns and trends in data to inform decisions.
Model data driven user interacts primarily with a mathematical model and its results while data driven DSS is user interacts primarily with the data
In a model-driven DSS, decision-making is based on predefined mathematical or statistical models, where users input data to generate output. In a data-driven DSS, decision-making is based on analyzing large volumes of historical data to identify patterns and trends, without necessarily relying on predefined models.
Datamart is primarily a stand-alone DSS that uses some type of model to perform "what-if" and other kinds of analyses.Visit http://www.prodigyhub.org for more such answers
Decision Support System (DSS) is a combination of software, data, and models, not a specific component. A DSS typically includes components such as a database, model base, user interface, and analytical tools.
The sales model is driven by advertisements.
Computerized decision support systems became practical with the development of minicomputers, timeshare operating systems and distributed computing. The history of the implementation of such systems begins in the mid-1960s. In a technology field as diverse as DSS, chronicling history is neither neat nor linear. Different people perceive the field of Decision Support Systems from various vantage points and report different accounts of what happened and what was important (cf., Arnott & Pervan, 2005; Eom & Lee, 1990b; McCosh & Correa-Perez, 2006; Power, 2003; Power, 2004a; Silver, 1991). As technology evolved new computerized decision support applications were developed and studied. Researchers used multiple frameworks to help build and understand these systems. Today one can organize the history of DSS into the five broad DSS categories explained in Power (2001; 2002; 2004b), including: communications-driven, data-driven, document driven, knowledge-driven and model-driven decision support systems. This hypertext document is a starting point in explaining the origins of the various technology threads that are converging to provide integrated support for managers working alone, in teams and in organization hierarchies to manage organizations and make more rational decisions. History is both a guide to future activity in this field and a record of the ideas and actions of those who have helped advance our thinking and practice. Historical facts can be sorted out and better understood, but more information gathering is necessary. This web page is a starting point in collecting more first hand accounts and in building a more complete mosaic of what was occurring in universities, software companies and in organizations to build and use DSS. This document traces decision support applications and research studies related to model and data-oriented systems, management expert systems, multidimensional data analysis, query and reporting tools, online analytical processing (OLAP), Business Intelligence, group DSS, conferencing and groupware, document management, spatial DSS and Executive Information Systems as the technologies emerge, converge and diverge. All of these technologies have been used to support decision making. A timeline of major historical milestones relevant to DSS is included in Appendix I. The study of decision support systems is an applied discipline that uses knowledge and especially theory from other disciplines. For this reason, many DSS research questions have been examined because they were of concern to people who were building and using specific DSS. Hence much of the broad DSS knowledge base provides generalizations and directions for building more effective DSS (cf., Baskerville & Myers, 2002; Keen, 1980). The next section describes the origins of the field of decision support systems. Section 3 discusses the decision support systems theory development that occurred in the late 1970s and early 1980s. Section 4 discusses important developments to communications-driven , data-driven, document driven, knowledge-driven and model-driven DSS (cf., Power, 2002). The final section briefly discusses how DSS practice, research and technology is continuing to
Sorta, hard to answer as you listed no model.
Model Driven Generation
Its business model
model driven dss is a decision support system used by managers,staff members and people who interact with the business organization for analyzing semistructured and unstructured decisions.they are usually deployed as software,hardware in standalone PCs.dss basically has 4 analysis models: 1) what if analysis 2)sensitivity analysis 3)goal based analysis 4)optimized analysis