Decision support system
...analysis, online analytical processing data is stored in a multidimensional database. A multidimensional database considers each data attribute like a product, as a separate dimension. Online analytical processing software has the ability to establish the intersection of dimensions. Like all products sold in a particular region above a particular price and display the results. An Online analytical processing database does not necessarily need to be as big as a data warehouse because not all transactional data is required for trend analysis by the system. OLAP commodities are characteristically designed for multiple-user environments, with the expenses of the software dependent upon the number of users. BI (Business Intelligence) Business intelligence has a number of applications for getting together, storing, analysing, and giving access to data to assist enterprise users make a lot better business decisions. Business Intelligence applications also comprise a number of other activities such as decision support systems, query and reporting, online analytical processing, statistical analysis, forecasting, and data mining. Business intelligence applications are known to be task orientated or designed to meet a special requirement and Mission-critical and integral to an enterprise's operations. There are several types of Decision support systems some of which are: File drawer system This is the most simple type of decision support system it allows you to produce access to data items. Data is integrated and then manipulated to help make a plausible decision. Optimisation systems This system allows you to estimate the effects of a number of different decision alternatives and it is based completely on optimisation models. This model can provide the best assignment schedule. Data retrieved and analysis for decision support These systems depend heavily on interaction with a current database system. (i) Simple entry and enquiry systems This supports decisions by supplying instantaneous query of a database for a particular enquiry. Some examples are airline booking systems and account enquiries system. (ii) Data analysis systems This basically provides summaries and selected reports of information held on a database. (iii) Accounting information systems Accounting information is provided as an evaluation of accounting transaction data. Some examples are a summary of balance sheets and profit and loss reports. Computational support for structured decisions This involves the use of data held on a database and computation jointly with details of single cases to help arrive at information for a possible decision. Decision support involving modelling This system depends on the use of current data from a database or user input data, which may be hypothetical. With the use of this information its implications are calculated with the use of a model. (i) Spreadsheet models are utilised to represent accounting relationships between numerical accounting data. One of the reasons they are used is to take the boredom out of budget preparation and forecasting. The awareness of the company to changes in the values of accounting information is fairly simple to assess by hypothetical ¡¥what if¡¦ changes. (ii) Probabilistic models bring together elements of probabilistic reasoning and risk analysis in their calculations of modelling. The Development of DSS The development of a decision support system takes into consideration the types of information and the facilities required for taking the decisions. DSS is decision led because details of the decision taking process are required. It is vital that the end users (decision takers) participate in the design process. Decision support systems are produced by packages specifically incorporating decision support development tools. In all approaches it is considered sensible to develop prototypes at first. The Cost and benefits of DSS The costs and benefits of a DSS are rather difficult to figure out, down to the fact that DSS concentrates on effectiveness rather and efficiency.. Peter G. Keen concluded that the decision to build a DSS appears to be based on value rather than cost. He outlined the benefits of a DSS as follows: 1. Increase in the number of alternatives examined. 2. Better understanding of the business. 3. Fast response to unexpected situations 4. Ability to carry out ad hoc analysis 5. New sights and learning 6. Improved communication 7. Improved control 8. Cost saving 9. Better decisions 10. More effective teamwork 11. Time saving 12. Making better use of data resources The benefits generated by a DSS are vague and are difficult to assess. However this quantification may be subjective, and different individuals may come up with different figures. The fact that DSS increases...