Data Mining Performance Improvement Classification

Question: Discuss about the Data Mining for Performance Improvement Classification. Answer: Introduction: AIH has initiated to use the Data mining technology for easing their operations and functions. They have initiated the process of financially supporting the students from financial point of view for making sure that they complete their studies and get degrees from AIH. They want to do all this without the involvement of the government. Determine Business Objectives: The objectives of the AIH organization for implementing data mining process are: New funding system: The AIH organization has planned to start a system where they would fund the students for pursuing their higher studies from the organization. There are many students who cannot complete their studies after high school due to lack of funds and shortage of educational scholarships by the Government. Hence, the AIH would form its own student funding sector without the help, support and involvement of the government for supporting the students to complete their studies. Increased data processing: The use of data mining would be helpful for collecting and managing the huge amount of data that have to be stored for providing the students with scholarships. Many information and personal details of the students including their family background must be stored and kept at the ease of access for funding the students to pursue the studies. Increase of students at AIH: AIH has the primary objective of incrementing the number of students in the AIH by the use of data mining and funding process. The use of the funding the students, AIH would be able to encourage more students to pursue their studies. Problem area: The process of data mining requires the management of technological advanced tools and techniques. The data mining provides the advantage of management of huge amount of data and information for business organizations (Mir Pinnington, 2014). However, data mining has some flaws like it is complex and not easy to understand, the technical requirements for the system is large in number, and the process requires exhaustion of considerable sum of money. The data mining requires skilled experts who have the experience and knowledge for the processes of data mining (Wu et al., 2014). The data mining process requires some specific tools (system configuration and access) and software (licensed with administrator permission). These tools and software have a reasonable price and it makes the data mining costlier from other processes. There are many universities and institution that are using the data mining as a tool for managing the data flow of their organization. According to Larose (2014), the use of the data mining tools and objects would assist the organization for maintaining their records and students information. AIH has initiated the student funding program in their organization and they need the use of data mining for managing the huge amount data and information that has to be processed for the new funding program. The motivational factor for the implementation of the data mining process in AIH was the need of an advanced system that could process he amount of data generated for the funding process of AIH. The organization had been using the information system for maintaining their records. However, there was no use of data mining within the organization. The process of funding the students requires the approval of the higher authorities of the AIH like investors, directors, and owners. The data mining process have to provide the report to the top management team of AIH. The top management had to give their permission and consent before the initialization of the funding process. However, the technicians and Information Technology experts would have to manage the data mining process in AIH. Business objectives: The data mining process would assist the AIH organization for easing the process of data management of all scales (small, medium and large) (Liu Motoda, 2012). The analysis of the students data and evaluating his or her chances for the education funding process could be benefited with the use of data mining process. However the organization has certain goals from the data mining process, such as- Increment in the number of students in the university Offering the students with the privilege of fees and living expenses Encourage more people like professionals, senior citizens, low income gainer, homemakers, and rural people to pursue their education Business success criteria: The success criteria of the project include the commercial success, meeting the users requirements, meeting the budget of the project, and managing the quality (Cserhati Szabo, 2014). The factors behind these success criteria are project mission, schedule and plan, top management support, and monitoring and feedbacks. The success criteria, assessor and specified business objective of AIH are provided in the table below- Success Criteria Assessor of the Criteria Specified Business Objective Commercial Success Students who would join the AIH for pursuing their studies Increment in the number of students in AIH Meeting the Users Requirements Technical team who have made the design and operation process of data mining Implementation of data mining process in the organization Meeting the Budget of the Project Investors who would invest in the project Getting the funds from different institutions Managing the Quality The organization AIH owner and other related personals Increasing the market reputation of AIH Assess situation Inventory of resources: The process of data mining would require various resources and they have been listed below- Types of Resources Resource Economic Resources: All the investments and sum of money used for covering the expenses on the data mining process are included in the project. Cash in forms of Investments, Capital, and Revenues Collected Human Resources: It covers the man strength (skill or manual) that is required for the completion of the data mining process. Technical support, data processing experts, and system designers Technical Resources: It covers the aspects of technology, data, software, and system requirements for the data mining process. Hardware (system configuration and devices), software (tools for data mining and processing), and data provided by the students Sources of data and knowledge: The data sources are the different study, research papers, and other materials that show the data and the method used for collecting the data (Liese et al., 2013). Secondary data is the sourced data that is being used by an individual and the data has been collected from practical experiments and researches done by someone else. Different types of data sources include socially available Research papers, Census reports, Survey, Online data archives, and Statistics reports can be sued for getting data on data mining performances. Knowledge sources are the researches and books from where knowledge on any particular topic can be gathered and used for their project (Agarwal Shah, 2014). The different types of knowledge sources include the empirical experiences (natural experiences and restricted observations), surveys and check sheet, and dissertations available for research purpose. Requirements, assumptions and constraints: The project of implementing the data mining process at the AIH for easing their operations and data management requires technical, economic and human resources. They have been listed below- Requirement of the project Description Cash and Assets The cash and assets are the primary requirement for the project (Majewicz Sampson, 2016). it is attained in forms of Investments (sum of money invested by different institutions), Capital (amount invested by the AIH owner), Revenues Collected (collected fees from students), and assets in form of land, building and other properties of AIH. Software The data mining requires some tools and software (licensed software) for operations of the data processing. Hardware The system configuration of the data mining consists of hardware requirements such as computing devices, storage device, and other peripherals. Human Skills The technician, data processing experts, and system designers for data processing would be required as the form of human support for development of the data mining processes. The security and legal issues of data mining include the phishing, unauthorized entry, spamming, and data theft. The schedule of the data mining project along with the comprehensibility and quality of outcomes are shown in the table below Operation of project Expected time duration Desired Outcomes Making plan for the Data Mining Process 2 days A plan for the project of data mining project is completed Designing the data mining system 14 days Design for the system of data mining process Implementing the data mining system 23 days System for data mining process is implied at AIH Alignment of the data mining process with AIH operations 7 days Operations of AIH and data mining has been aligned on same platform The assumptions that were made in the project of data mining implementation at AIH are presence of technical support (skilled experts of data mining process), abundance of favorable system tools (licensed software for data mining), and integrity of information (students data would be concise and clear). The constraints of the project were shortage of time, no previous knowledge of data mining, and exhaustion of resources (Xu Moon, 2013). The non checkable assumptions include the possibility that all the team members were compatible to work with each other and there was no other issue in knowing whether the investors were dissatisfied from the project. The risk factors and their contingency planning has been shown in the table below Risk factor Conditions of Risk factor Contingency Planning Management issues The data mining is completely based on technological development of the AIH (Lin, Cercone, 2012). Hence the management of the project operations would require technically skilled members. Plan for project operations should be developed from the use of the project management tools and techniques Investor dissatisfaction towards security issue The growth of dissatisfaction among investors due to the security issues of data mining could result in creating technical reasons. Secured design for the data mining process should be used for the operations at AIH Bad debts The funding of the students can result in bad debts for AIH. The students might not be able to payoff later due to some reasons and it is the financial risk for AIH. Some provisions for bad debts must be made which could be used for minimizing the loss from bad debt Data Redundancy The data stored in the data mining database can result in creation of data redundancy (duplications of data). System integration would help in detecting redundant files Government interference The government was not involved in the project. however, for the lack of showing government concern can act as the business risk The project plan charter should be submitted to the government Determine data mining goals Determine data mining goals: The benefits of data mining in an organization include the advantage of marketing, financial operations, large scale data management, and increase in production. AIH has got the above mentioned benefits for their operations and achieving their goals. The data mining goals of AIH includes- Short Term Goals- ease the operations of student data processing, improve the efficiency of admission in AIH, and making the investors clear about the objectives and progress of AIH are the short term goals of the data mining project. Long Term Goals- Increasing the efficiency of operations for getting maximum reputation and developing scope for global based data processing are the long term goals for the data mining project. Intended output of project- The intended output of the project includes the formation of a system process for data mining operations. The data mining would help in cluster detection process in AIH that would be useful for the recognition of the pattern in the large data sets of the students information. The operations of data mining would be useful in AIH for improving the function of admission process of students. The technical benefits of data mining include the accessibility, scalability, performance improvement, and integrity. Problems of data mining: The problems of data mining in AIH include complexity, security issues, and costing. The problems of the data mining are the result of operations requirements and system development. The large scale operations would be responsible for the increasing of the data mining complexities. The data mining has to face issues of security and data lost. The problems of data mining also include- Classification Description Prediction Technical Problems Data redundancy Design failures Complexity Huge amount of data makes data redundancy more probable and effective Ethical Problem Security issue Unauthorized entry The flaws in security has been a result of designing errors and provided the scope for unauthorized entry Bibliography Agarwal, R., Shah, S. K. (2014). 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