evaluate and distribute needed timely and accurate information to marketing

Evaluate and distribute needed timely and accurate

This preview shows page 38 - 40 out of 72 pages.

evaluate, and distribute needed, timely, and accurate information to marketing decision makers." The terms MIS and information system are often confused. Information systems include systems that are not intended for decision making. The area of study called MIS is sometimes referred to, in a restrictive sense, as information technology management . That area of study should not be confused with computer science . IT service management is a practitioner-focused discipline. MIS has also some differences with ERP which incorporates elements that are not necessarily focused on decision support. Any successful MIS must support a business's Five Year Plan or its equivalent. It must provide for reports based upon performance analysis in areas critical to that plan, with feedback loops that allow for titivation of every aspect of the business, including recruitment and training regimens. In effect, MIS must not only indicate how things are going, but why they are not going as well as planned where that is the case. These reports would include performance relative to cost centers and projects that drive profit or loss, and do so in such a way that identifies individual accountability, and in virtual real-time. Anytime a business is looking at implementing a new business system it is very important to use a system development method such as System Development Life
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Cycle. The life cycle includes Analysis, Requirements, Design, Development, Testing and Implementation Data mining: Data mining is the process of discovering interesting and useful knowledge from large amounts of data warehouses. The architecture of a typical data mining system as given by jiawci Han and Michelin Kamber in their book Data mining concepts and Techniques (2001), consists of the following components as shown in fig Database or data warehouse or other information repository: This includes one or more databases, a data warehouse, or any other information repository. Data cleaning and data integration techniques have to be applied to the data before the data mining algorithm can be applied on it. However, in case the Data mining algorithms are applied directly on the: Data warehouses, then cleansing and integration functions may be skipped because a data warehouse already contains integrated and cleansed data. Database or data warehouse server: The database or data warehouse server is used to fetch the relevant data, based on the user’s data mining request. Knowledge base: It contains the domain knowledge that is used to guide the search or used for evaluation of the interestingness of resulting patterns. Such knowledge can include concept hierarchies, user beliefs, and interestingness of resulting patterns. Such knowledge can include concept hierarchies, user beliefs, interestingness thresholds and the metadata.
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