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Digg it UP - Decision Support System : A Snap Shot
Delegate Or Die: 6 Steps For Business Growth sion support systems (ODSS) evolved from the single user and model-oriented DSS. Beginning in about 1990, data warehousing and on-line analytical processing (OLAP) began broadening the realm of DSS. As the turn of the millennium approached, new Web-based analytical applications were introduced.To achieve business growth, you need to focus on your strengths and hire others to take care of the rest.Unfortunately, entrepreneurs often fail to employ this fundamental business growth strategy.Whether it’s driven by pride or fear, I meet many entrepreneurs who have difficultly delegating, including recently: a fashion designer who won’t let go of her accounting; a pastry chef who refuses to let designers get near his website; and a furniture maker who turns down professional help to arrange his storefront.“To be good at business does not mean you have to be good at everything,” suggests Mark Wardell, President and Founder of Wardell Professional Development, which helps businesses across North America attain sustained growth.So how do you overcome this common roadblock? Wardell says it’s a matter of placing It is clear that DSS belong to an environment with multidisciplinary foundations, including (but not exclusively) database research, artificial intelligence, human-computer interaction, simulation methods, software engineering, and telecommunications. Historical In a more precise way, it can be defined as: "An interactive, flexible, and adaptable computer-based information system, especially developed for supporting the solution of a non-structured management problem for improved decision making. It utilizes data, provides an easy-to-use interface, and allows for the decision maker's own insights." DSS are computer-based support for management decision makers who are dealing with semi-structured problems. With respect to computer terminology it can be defined as: "Interactive computer-based systems that help decision makers utilize data and models to solve unstructured problems." Though, it is impossible to give a precise definition including all the facets of the DSS. Nevertheless, the term decision support system remains a useful and inclusive term for many types of information systems that support decision making. Every time a computerized system is not an on-line transaction processing system (OLTP), someone will be tempted to call it a DSS. As it can be see that there is no universally accepted definition of DSS. Additionally, the specifics of it is what makes it less generalized and more detailed. In addition, a DSS also is a specific Software application that helps to analyze data contained with a customer database. This approach to customers is used when deciding on target markets as well as customer habits. History of DSS The concept of decision support has evolved from two main areas of research: the theoretical studies of organizational decision making done at the Carnegie Institute of Technology during the late 1950s and early 1960s, and the technical work on interactive computer systems, mainly carried out at the Massachusetts Institute of Technology in the 1960s. It is considered that the concept of DSS became an area of research of its own in the middle of the 1970s, before gaining in intensity during the 1980s. In the middle and late 1980s, executive information systems (EIS), group decision support systems (GDSS), and organizational decision support systems (ODSS) evolved from the single user and model-oriented DSS. Beginning in about 1990, data warehousing and on-line analytical processing (OLAP) began broadening the realm of DSS. As the turn of the millennium approached, new Web-based analytical applications were introduced. It is clear that DSS belong to an environment with multidisciplinary foundations, including (but not exclusively) database research, artificial intelligence, human-computer interaction, simulation methods, software engineering, and telecommunications. Historical d "Interactive computer-based systems that help decision makers utilize data and models to solve unstructured problems." Though, it is impossible to give a precise definition including all the facets of the DSS. Nevertheless, the term decision support system remains a useful and inclusive term for many types of information systems that support decision making. Every time a computerized system is not an on-line transaction processing system (OLTP), someone will be tempted to call it a DSS. As it can be see that there is no universally accepted definition of DSS. Additionally, the specifics of it is what makes it less generalized and more detailed. In addition, a DSS also is a specific Software application that helps to analyze data contained with a customer database. This approach to customers is used when deciding on target markets as well as customer habits. History of DSS The concept of decision support has evolved from two main areas of research: the theoretical studies of organizational decision making done at the Carnegie Institute of Technology during the late 1950s and early 1960s, and the technical work on interactive computer systems, mainly carried out at the Massachusetts Institute of Technology in the 1960s. It is considered that the concept of DSS became an area of research of its own in the middle of the 1970s, before gaining in intensity during the 1980s. In the middle and late 1980s, executive information systems (EIS), group decision support systems (GDSS), and organizational decision support systems (ODSS) evolved from the single user and model-oriented DSS. Beginning in about 1990, data warehousing and on-line analytical processing (OLAP) began broadening the realm of DSS. As the turn of the millennium approached, new Web-based analytical applications were introduced. It is clear that DSS belong to an environment with multidisciplinary foundations, including (but not exclusively) database research, artificial intelligence, human-computer interaction, simulation methods, software engineering, and telecommunications. Historical Additionally, the specifics of it is what makes it less generalized and more detailed. In addition, a DSS also is a specific Software application that helps to analyze data contained with a customer database. This approach to customers is used when deciding on target markets as well as customer habits. History of DSS The concept of decision support has evolved from two main areas of research: the theoretical studies of organizational decision making done at the Carnegie Institute of Technology during the late 1950s and early 1960s, and the technical work on interactive computer systems, mainly carried out at the Massachusetts Institute of Technology in the 1960s. It is considered that the concept of DSS became an area of research of its own in the middle of the 1970s, before gaining in intensity during the 1980s. In the middle and late 1980s, executive information systems (EIS), group decision support systems (GDSS), and organizational decision support systems (ODSS) evolved from the single user and model-oriented DSS. Beginning in about 1990, data warehousing and on-line analytical processing (OLAP) began broadening the realm of DSS. As the turn of the millennium approached, new Web-based analytical applications were introduced. It is clear that DSS belong to an environment with multidisciplinary foundations, including (but not exclusively) database research, artificial intelligence, human-computer interaction, simulation methods, software engineering, and telecommunications. Historical It is clear that DSS belong to an environment with multidisciplinary foundations, including (but not exclusively) database research, artificial intelligence, human-computer interaction, simulation methods, software engineering, and telecommunications. Historical It is clear that DSS belong to an environment with multidisciplinary foundations, including (but not exclusively) database research, artificial intelligence, human-computer interaction, simulation methods, software engineering, and telecommunications. Historical development The role of business information systems has changed and expanded over the last four decades. In the incipient decade (1950s and '60s), “electronic data processing systems” could be afforded by only the largest organizations. They were used to record and store bookkeeping data such as journal entries, specialized journals, and ledger accounts. This was strictly an operations support role. By the 1960s “management information systems” were used to generate a limited range of predefined reports, including income statements (they were called P & L’s back then), balance sheets and sales reports. They were trying to perform a decision making support role, but they were not up to the task. By the 1970s “decision support systems” were introduced. They were interactive in the sense that they allowed the user to choose between numerous options and configurations. Not only was the user allowed to customize outputs, they also could configure the programs to their specific needs. The main development in the 1980s was the introduction of decentralized computing. Instead of having one large mainframe computer for the entire enterprise, numerous PC’s were spread around the organization. This meant that instead of submitting a job to the computer department for batch processing and waiting for the experts to perform the procedure, each user had their own computer that they could customize for their own purposes. Many poor souls fought with the vagaries of DOS protocols, BIOS functions, and DOS batch programming. As people became comfortable with their new skills, they discovered all the things their system was capable of. Computers, instead of creating a paperless society, as was expected, produced mountains of paper, most of it valueless. This information overload was mitigated somewhat in the 1980s with the introduction of “executive information systems”. They streamlined the process, giving the executive exactly what they wanted, and only what they wanted. The 1980s also saw the first commercial application of artificial intelligence techniques in the form of “expert systems”. These programs could give advice within a very limited subject area. The promise of decision making support, first attempted in management information systems ba
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