Decision support system
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Decision support system

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Decision support system Decision support system Presentation Transcript

  • DECISION SUPPORT SYSTEM and OLAP PRESENTED BY: BHUWNESHWAR PANDAYA
  • DEFINITION DSS give direct computer support to managers during the decision-making process. DECISION SUPPORT SYSTEM provides interactive ad hoc support for the decision making process of managers and other business professionals. EXAMPLES: product pricing, profitability forecasting, and risk analysis systems etc.
  • …….. DECISION SUPPORT SYSTEMS are computer-based information systems that provide interactive information support to managers and business professionals during the decision making process. DSSs use:1) Analytical models,2) Specialized databases,3) A decision makers own insights and judgments,4) An interactive, computer based modeling process to support semi structured business decisions.
  • Components of DSS Legacy Web Other software browser softwares .. User Interface Functions Hyperlinked Multimedia, 3D Visualization Model Management Functions Analytical Modeling, Statistical Analysis Data Management Functions Data extraction, validation, Sanitation, integration, and replication Operation Market Sales Customer al Data Data Data a/c data
  • Difference b/w DSS & MIS MIS DSS Provide information about Provide information and•Decision support the performance of the decision support provided organization techniques to analyze specific problems. Periodic, exception, Interactive inquiries and• Information form demand, push reports and responses and frequency responses Prespecified, fixed format Ad hoc, flexible and• Information format adoptable formatInformation Information produced by Information produced byprocessing extraction and manipulation analytical modeling ofmethodology of business data business data.
  • Using DSS: A decision support system involves an interactive analytical modeling process. There are four basic types of analytical modeling activities are involved in using a DSS:I. What-if analysis ,II. Sensitivity analysis,III. Goal-seeking analysis, andIV. Optimization analysis.
  • ….Type of AnalyticalModeling Activities and examples Observing how changes to selected variables affect other variables.What-if analysis Example: what if we cut advertising by 10%? What would happen to sales. Observing how repeated changes to a single variable affect other variables.Sensitivity analysis Example: Let’s cut advertising by 100% repeatedly so we can see its relationship to sales. Making repeated changes to selected variablesGoal-seeking analysis until a chosen variable reaches to a target value. Example: Let’s try increases in advertising until sales reach Finding an optimum value for selected variables, given certain constraints.Optimization analysis Example: What’s the best amount of advertising to have, our budget and choice of media?
  • Online Analytical Processing [OLAP] OLAP enables managers to examine and manipulate large amounts of detailed and consolidated data from many perspectives. OLAP involves analyzing complex relationship among thousands or even millions of data items stores in a data marts, data warehouses and multidimensional databases to discover patterns and trends etc. It provides fast answers to complex queries
  • ….. OLAP server CorporateClient PCs databases Multi- Dimensional databasesSpreadsheet data are retrieved Operational databasesStatistical packages from corporate databases Data martsWEB-enabled and staged in an OLAP Data warehouseOLAP software
  • OLAP involves – Consolidation: the aggregation of data.e.g. Data about sales offices can be rolled up to the district level, and district level data can be rolled up to provide state-level perspective. Drill-down: the reverse direction and automatically display.e.g. The sales by individual products or sales reps that make up a region’s sales totals could be easily accessed. Slicing and Dicing: ability to look at the database from different viewpoints. Slicing and dicing is often performed along a time axis to analyze trends and find time based patterns in the data.
  • OLAP examples….Common business areas where OLAP can solve complex problems include: Marketing and sales analysis Database marketing Budgeting Financial reporting and consolidation Profitability analysis Quality analysis etc.
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