ISY310 - Business Analysis | Data mining

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Added on 2019-10-31

ISY310 - Business Analysis | Data mining

Added on 2019-10-31

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1Business AnalysisStudent IDStudent NameUniversity Name

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2Contents1.Business understanding:.....................................................................................................31.1 Business objectives:..........................................................................................................41.2 Assess situation:...............................................................................................................51.3 Data mining goals:............................................................................................................8References..................................................................................................................................8

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3Introduction:One of the significant elements that should be searched for in a data mining application is todetermine the reason for which the study is implemented. Data mining is utilized forproliferation of novel forms of knowledge from the existing business knowledge. Theexisting process model for data mining is reliant on the use of CRISP-DM reference modeland the life cycle of the data mining project involves the distinct phases involved in theproject, the relevant tasks involved in the phases and the interrelationship between thedifferent tasks. Relationships among the different tasks in a data mining project areprofoundly dependent on the goals as well the background of the data mining project and thesignificance of the data to the user (Bhattacharyya, 2015). From the perspective of a data mining consultant, the illustration of this report could providecredible insights for the AIH in determination of problem areas that could result in failure ofits initiative known as, “We can pay you to study now”. The foremost process involved in thedata mining process is business understanding which emphasizes on comprehending theproject objectives and the requirements from the perspective of a business. Businessunderstanding could also be apprehended as the comprehension of the business about itsbackground and objectives (Fleisher & Bensoussan, 2015). The business understandingprocess is also associated with translation of information related to project objectives andrequirements into the definition of a data mining problem. The data understanding processfollows the business understanding process which involves collection of initial data present inthe existing database of the institution. Data understanding provides insights into the data andthe quality issues that could be identified in the student information. The data preparation tasks are required to be performed multiple times involving thetransformation of the existing data into a new format. The following stage of the businessunderstanding refers to modelling which could be realized in the case of AIH throughestablishing specific parameters according to optimal values. Evaluation stage in the businessunderstanding could be associated with the review of the model’s capacity to addressbusiness objectives of AIH (Foorthuis & Brinkkemper, 2015). The results obtained from thedata mining model should be reviewed in terms of their application in context of the businessobjectives. The final stage of business understanding would involve deployment which refersto the organization of the data and representing in a feasible manner to the institution.

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