Business Plan Using Business Analytics †MyAssignmenthelp.com

Question: Discuss about the Business Plan Using Business Analytics. Answer: Introduction The present report is mainly focused on the creation of the business plan using business analytics with data mining process. As in the given scenario, it is seen that the AIH is considering providing assist for its students with not using the government funds. The main objective of the AIH is to develop its own financing program in order to provide the fund to the students. Therefore, the present report is mainly emphasized upon the finding organization objectives and success criteria. Moreover the report also focused on the how business uses the data mining tools to accomplish its set of objective. Business understanding Business objective The main objective of the business is to accomplish better competitive advantage and increase the student enrolments. This would help the organization to achieve higher amount of revenues from the market. Moreover, the association also focused on encourages students and other potential groups to study in university without worrying about the money related with the studying; this is also considered one of the vital objectives of the business. Problem areas According to the Micek Pacholczyk, (2017), Marketing and business development is considered the main problem areas of the organization. Since the organization primary purpose is to offers money to students in their studying time, therefore the business development plans helps the organization to determine that is it is profitable project or not for the organization. As said by the Siuly, et al., (2017), the organization also required to gather huge amount of data and findings an effective decision regarding the success of the project and this is not an easy task for the organization. Sources of financing also considered the main problems for the organization. Therefore to solve this issue AIH needs to incorporate data mining tools and techniques that assist them to find out the optimum simulations among the several alterative. The main motivation factors of this project are that they accomplish better brand name and success in competition market. Apart from that, if project is success then they attracts both national and international students that will helps them to increase profits from the enrolments and enhances in the market image in positive manner. From the evaluation of the business scenario it is seen that organization is not uses the data mining tools. The main target group of this project is students (both national and international) and other potential groups (rural residents, low income earners). Business objectives The main objective of the customers is to achieve financial amount (studying for a degree) from the organization in very low of internet. Apart from that, the primary objective of the organization to retain the customers by predicting when business is prone to move to competitors. Moreover the secondary objective of the organization is to find attract the customers from both national and international market that would help them to generate better revenues. Moreover the other purpose of the organization might to find out whether low fees influence only one particular segment of consumers. Therefore, as a data analysts I recommended that the organization needs to implement the data mining process that helps them to solving business issues in financing by finding causalities, correlations and patters in business information as well as market prices, that is not effectively apparent to the management because data volume to too large. Use of this tools in business, not only helps the organization to retain more customers but also helps to find out the credit risks, market risks, control and portfolio management in better manner. Business success criteria The business success criteria are to improve the productivity and improved customers satisfaction. The key success of the business is to retain more customers and provide better quality of services that customers are achieved. Therefore from the analysis and findings it is said that the main business success criteria are following; Increase performance( enrolment rate) by 18% from FY2017 to FY2018 Capture the market share of 12% within 24 months Reach the sales volumes of $10000000 within 24 months Assess solutions : Inventory of resources Human resource of present business development plan is following; Expert data analyst and business analysts Data mining engineers Technical support engineers In order to make better decision making procedures and success the business the organization needs to implements knowledge management system that involves data such as live warehouse and functional data, fixed extracts data and past data. Apart from that the organization needs to computer resources which includes the software system i.e. data mining software and computing resources such as hardware platforms. Sources of knowledge and data In present technology era sources of data play the vital roles as it helps the organization to make better decision making process in critical situations. Therefore in order to accomplish set of objective in successful manner organization/data analysts needs to uses different type of sources, which includes the written documents, excerpts data and online sources. Study conducted by the Cupek, (2017), data analysts main objective is to determine out the relationships and patterns in the data and applied the statistical techniques to find out whether there is any relationship exit better variable of not. Therefore, to accomplish the relationship between the low fees structure and organization performance, data analysts mainly implements different tools and techniques such as Google fusion tables, Rapidminer, Knime, Solver etc. Most of the data analysts use the R software that helps them to find out the relationship between the variables in better manner. As, the primary objective of th e organization is to accomplish better profits and retain more customers; this can be accomplished in better manner using these tools. As said by the Braun et al., (2017), Use of the data analysts techniques organization analyzes spending and withdrawal patterns to prevent identify theft and fraud. In addition to this, it also aids to find out the risks associated with the project in better manner. Assumptions, requirements and constraints Project completion Starting date of the project: 12-Novemnber-2017 Ending date of the project: 12-Novemeber-2018 Quality and comprehensibility of result In order to achieve better quality of outcomes data analysts mainly implements data i.e. both real time and past time data that helps them to find out the effective outcomes. Moreover, to gain achieve comprehensibility, data analysts store the all results in organization database from where the manager continuously monitor the development performance. Security and legal issues Security is considered the main issues in this development plan, because all the decision was made using findings of the available data and information. Therefore to solve this problem organization needs to implements password protection techniques, dual firewall techniques in database system (Chen et al., 2017). On the other hand organization needs to restrict users to access their data warehouse. The analysts mainly stored customers information in data base and findings optimum situations; therefore in such situation legal issues have been raised because without customers information organization has not any authority to use and analyze them. Thus to solve this problem is better manner the organization incorporates all ethical rules and regulations. Moreover, the organization respects individuals privacy in better manner. List of assumptions The team members of the development plan possess the desired competence for their job Demand of the students regarding the interests finance is continuously increases No economic disaster and major shift of the technology Validity of the results Constraint lists Constraints lists of the development plan are following; Accomplishing sufficient supplies and accommodations Timing and scheduling issues:- If the project i.e. development plan in not completed within the time limit then the organization not achieve its success criteria Costs associated with the data mining tools and techniques is high; therefore it is also considered the main constraint of the development plan Technical performance also considered one of the vital constrains because business success criteria is mainly based on the findings of the data. Lack of resources as well as skills on the part of the team members Lists of the risks Risks lists components project scope risks not well defied project scope, high complexity, no project charter Design and specification risks unrealistic specification, poor planning and designing Time risks not complete proper work break down structure, not effective database, high costs and resources Costs risk Contingency plan IT is an alternative plan that is mainly used of a possible foreseen risks event come in project. Therefore contingency plan is mainly represents preventive action that mitigate and decreases the negative impact of the risks. Issues associated with the project Action to be taken to solve Funding dependent upon the outcomes of data mining In order to solve these problems in more effective manner data analysts needs to recheck all the available outcomes in better manner. Moreover, Analysts needs to implement proper data analysis tools and techniques that reduce the error of data mining findings. Data sources The decision of the development plan is mainly based on the data sources, therefore to accomplish better outcomes data analysts needs to use data from appropriate website and government website (Studeny et al., 2017) Apart from that before selection of the data, analysts must have to ensure that data is reliable and viable. Competioror comes with better solutions If the competitor comes with the better solutions then the organization needs to modify their objective and development plan. funding problems Funding also considered that main problems; therefore to solve this problems organization needs to move different sources of finance such as bank loan. Determine the data mining objectives The main objective of the data mining is to find out the structure data from unstructured data that helps the organization in decision making procedures. Another objective of the data mining is to find out the patterns in apparently random information and utilize all this data to better gain and understand patterns, trends and correlations and finally find out the customers interest towards the development plan. Moreover data mining also helps the organization to find out how many profits the organization achieve from development plan and how many widget a consumers purchase given their purchasers over the previous years. Business objective into data mining objective The main objective of the organization is to attract customers from the international and national; therefore use of data mining process organization implements marketing campaign that helps them to determine the customers segment in better manner. Moreover analyzing of the available data and information data analysts effectively find out the size of the segment (Hou, Guo Nevin, 2017). The main issues of the data mining process are mining methodology and user interaction, performance issues and diverse data types issues. Mining distinguish type of knowledge from the database is not easy. Moreover pattern evaluation also considered one of the main issues of data mining. References Cupek, R., Duda, J., Zonenberg, D., Ch?opa?, ?., Dzi?dziel, G., Drewniak, M. (2017, September). Data Mining Techniques for Energy Efficiency Analysis of Discrete Production Lines. InConference on Computational Collective Intelligence Technologies and Applications(pp. 292-301). Springer, Cham. El Sibai, R., Chabchoub, Y., Chiky, R., Demerjian, J., Barbar, K. (2017, September). Assessing and Improving Sensors Data Quality in Streaming Context. InConference on Computational Collective Intelligence Technologies and Applications(pp. 590-599). Springer, Cham. Braun, P., Cuzzocrea, A., Keding, T. D., Leung, C. K., Padzor, A. G., Sayson, D. (2017). 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