Business intelligence computing issues


" Business Intelligence " (BI) is a business management term that refers to applications and technologies used to gather, provide access to, and analyze data and information about their company operations. Business intelligence systems can help companies have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations, and they can help companies to make better business decisions. Elaborate Information Technology networks enable users to extract data (demographic and transactional) into structured reports, which can be distributed throughout an enterprise via intranets. Today the competitive forces prevailing in the world of commerce require firms to operate as efficiently and productively as possible in order to maintain and enhance market share, profitability and shareholder value. An essential element to achieving success involves the continuous enhancement of knowledge and understanding the business environment by all levels employees. Business intelligence is a constant routine of extracting corresponding information, creating and distributing accurate reports and updating cubes for information consumers to analyze, identify successes and failures and take appropriate actions. It is a continuous process of implementing policy and receiving how those policies either successfully or ineffectively achieved the goals they were set and to attain results in increased efficiencies for the organization. Business Intelligence incorporates analytical technology that produces forecasts and identifies cause and effect relationships corresponding to a particular business scenario. At this level, business intelligence involves the utilization of data mining. The term data mining today is characterized as the technology that incorporates the application of statistical techniques in conjunction with mathematical formulae that attempt to identify significant relationships between variables in historical data, which can then be used to forecast, perform sensitivity analysis, (e.g., what happens to someone's target/dependent variable when he/she changes one or more of his/her explanatory/independent variables) or just identify significant relationships that exist in the data at hand. Some of the common methodologies that make up the world of data mining include: (a) Clustering, (b) Segmentation and classification, (c) Neural networks, (d) Regression, and (e) Association analysis. Data storage, extraction and report writing technology helps users access and transform vast amounts of information located in data warehouses to a more user friendly format that creates business related reports in a timely fashion. As a result, the vast number of consumers of static reports within an organization receives information that corresponds to their functional areas in a timelier manner. …

DOI: 10.1145/1286460.1286461

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@article{Saha2007BusinessIC, title={Business intelligence computing issues}, author={Goutam Kumar Saha}, journal={Ubiquity}, year={2007}, volume={2007}, pages={4:1} }