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Data Mining for Business Intelligence - Case Study Example

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The paper "Data Mining for Business Intelligence" proves the importance of data mining is its capacity to realize legitimate, novel, ultimately important, and completely comprehensible trends in data preserved in the databases especially the structured ones…
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Data Mining for Business Intelligence
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Extract of sample "Data Mining for Business Intelligence"

?Business Intelligence       Business Intelligence Data mining is an important process in every business initiative and to the entire organization process. The importance of data mining is its capacity to realize legitimate, novel, ultimately important and completely comprehensible trends in data preserved in the databases especially the structured ones. Business intelligence incorporates the tools as well as the systems which perform vital functions in the strategic reorganizational processes of the company. The systems in the business intelligence enable the corporation to collect, saves, view and evaluate to assist in the process of decision making. The systems are diverse and highlight every perspective of the business such as the customer profiling and support, market segmentation and research and statistic evaluations among others. Several companies gather enormous quantities of information from their various business processes. The collection of data of such quantities enables the business to determine the problems facing the organizations in its desire to fulfill the needs of its customers and the understanding the quality of their services. The desires of providing best quality of products and provision of outstanding services to the customers might demand the use of many software programs especially in data mining and data entry. Here, there will be detailed analysis of the business intelligence with respect to human resource functions. Therefore, the piece would provide suitable solutions to problems such as employee absenteeism, delays to the customers and the associated complaints. Generally, there will be the analysis of the application of business intelligence to ensure ideal operations of a business organization. Nonetheless, it is essential to understand that business intelligence depends on data mining to a greater degree. The learning organization might result in an organization in the situation where the company promotes the learning processes among its members together with constant transformation. The learning business is compelled with the forces of competition that tend to assess its capability to deliver desirable services and its capacity to maintain its position in the competitive market situation. Applications of Mashups Mashups are essential in every organization due to their relevance and capacity to execute desirable functions in an organization. There are server based and web based mashups grouped according to the source of data, analysis and reformatting of information. The functionality of the mashups are based on three main components – the presentation, web services and data. Mashups include the applications, which reuse and join information together with services that are present online and they are created in a sudden ad-hoc manners to facilitate automation of procedures together with remixing the data. Mashup creation promotes faster, easy and affordable program creation by reusing resources that have been developed already, evaluated, and catered for by the large quantity of raw material found on the Web. The Use of Mashups in Human Resource In human resource, staffing is the essential element that determines the performance in an organization. Mashups are capable of upholding all the staffing features due to its ability to fit their functionalities. The components considered in the Mashups creation entail selection, human resource planning, job evaluation and recruitment. Mashups are useful in the evaluation of time and attendance of the employees. Mashups have automation feature that computerizes the activities of the managers. The Masups are capable of determining the time frame within which particular staff reported and or engaged in given activities. This system is capable of collecting information on ideal time and activities-related engagements. The system is also composed of a searching capability, which enables it to find the information of an employee in the profile category and opt for the allocation of work. Labor distribution may also appear to be a task in an organization that can be performed by the automated systems of the Mashups. The visualization feature of the Mashups enable for the acquisition of the raw data from variant sources online as well as the business sources and amalgamate them into a comprehensive combination of the operations, hence generating a complete database of data. This enables the organization to have full approach to all the information that might also be demanded for use in human resource department of the organization especially in the analysis of resumes. The use of Mashups in commercial aspects   The mashups are essential in the retrieval of information from various sourses on the web. This is important in the generation of data that can be used in the business commercially. The fundamental components of an organization include customers and the associated quality of products or services they obtain. The systems provide the data on the sales of products as well as the utilization of the organizational services by the consumers. The information concerning the quantity of sales made by a company is available via the systems. Besides the sales the quantities can be evaluated with respect to the prices and overall estimates obtained automatically. The data mining process aids at the provision of valid and comprehensive information through the mashups. Whenever sales are made on automated systems, the information on the item and the customer location are obtainable. In a business setup, the information on the location onto which the items were sold can be used to determine the decision making process and the reorganizations for the market segmentation procedures. Therefore, the organization can know the quantities to supply to different destinations. In the situation of a small taxi company and the Eddie Stobart, then this would provide a distinct disparity due to the amount of data processed and availed to the users. Being that Eddie Stobart is a larger organization as compared to the taxi company in the situation, the nature of data presentation may vary since the retrieval of data from the databases of the different locations would be different and the loading time as well on the web. Nonetheless, the information will be important especially at the point where logistics between the larger and the smaller corporate might be necessary. The logistics in the two situations have to be different because the firms have got different quantities of data to manage in their database systems. In the first situation of the smaller taxi company, there might be no complications concerning the type of their databases. This is because, the company is smaller and has few or no branches. In this case, the consideration is that the taxi company has no branches and that the management of its inventory is not complicated. In this situation there might only be a simple database that only consider the deployment of the company's vehicles to their designated locations with respect to time. When the employees (drivers) return the vehicles after their operations, then their mishups as well as the systems will indicate the information to the administrator. The data stored in this situation and that is entitled for the management might be linear and no multi dimension might be required. Conversely, the Eddie Stobart company would be comprehensive in its logistics. In the first case, the company has different types of 'vessels' for carriers – there are trucks and trailers. The company vehicles have different capacities. The trailers have a greater capacity for carrying commodities and this means that the weight carried differ. The vehicles carry products to different destinations eithin the city, outside the towns and might also transverse to the destinations beyond one state. The operators in every truck might be two or more. The situation in Eddie Stobart is totally dissimilar to that of the taxi company. Therefore, the performance of the mishups in this case are anticipated to be more complex. For instance, in the Eddie Stobart's database, there will be columns of the type of commodity transported, the quantity, the weight, the destination, number of operators and the type of the carrier. The system is therefore expected to display the full information concerning the whole process. The mishups assigned for the performance of this function is expected to scroll all the information in all databases in the web and display it to the user. Feeding of this information in the company might be manual done by the staff after verification by the relevant personnel. The organizations can learn from their daily experiences with the respective situations hence can customize their business intelligence systems to cope up with every situation for normal functioning and satisfaction of the customers. The organization learning in this situation will assist in providing the organization staff with the required information and training that are necessary in performing their normal chores successfully. In the situation of full attainment of the required skills and expertise ranging from competence to proficiency among the workers, they will be able to perform their tasks well in a manner that fully satisfies the customer's needs. Conclusion throughout this exercise, there has been a full evaluation of the data mining, the organization learning and the business intelligence together with their interconnections and role in the business organization. The analysis has provided th manner in which the business intelligence systems aides the business in ensuring that it tolerates all the compulsions of the external environments in the business and specifically, competition. The data mining process enables the business to remain relevant in its niche and resistant to all forces in the market. In case of the company, there must be relevance seeked and attained through the business intelligence in the overall industry. Therefore, all the problems facing an organization such as the human resource management issues of the employees, the sales-inventory management as well as the customer satisfaction especially with respect to time management and convenience. The customers are the basis of the business and the manner of their satisfaction matters and when the customers are fully satisfied then the business must remain competent in the market. Data mining is core. References Shmueli, G., Patel, N. R., & Bruce, P. C. (2011). Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel(r) with XLMiner(r). Chicester: John Wiley & Sons. Kudyba, S., & Hoptroff, R. (2001). Data mining and business intelligence: A guide to productivity. Hershey, Pa. [u.a.: Idea Group Pub. Vercellis, C. (2013). Business intelligence: Data mining and optimization for decision making. Hoboken, N.J: Wiley. De, V. B. (2006). Decision trees for business intelligence and data mining: Using SAS Enterprise Miner. Cary, NC: SAS Institute. Thuraisingham, B. (2003). Web Data Mining and Applications in Business Intelligence. London: CRC Press. Thierauf, R. J. (2001). Effective business intelligence systems. Westport, Conn. [u.a.: Quorum Books. Blokdijk, G. (2008). Business intelligence 100 success secrets: 100 most asked questions: the missing BI software, tools, consulting and solutions guide. Dayboro, Qld: Emereo Pty Ltd.. Surma, J., Go?rniakowska, M., & Gee, P. (2011). Business intelligence: Making decisions through data analytics. New York, N.Y: Business Expert Press. Sabherwal, R., & Becerra-Fernandez, I. (2009). Business intelligence. Hoboken, N.J: Wiley. Read More
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