Business case understanding | My Assignment Tutor

UnitAssessment TypeAssessment NumberAssessment NameWeightingAlignmentwith Unitand CourseDue Date and TimeGroup AssignmentA3Business case understanding (Business analysis report based on data miningconcepts)15%ULO1, ULO3, ULO4Assessment Description The goal of this assessment is to develop the business analysis skills of the studentsthrough a real-world scenario. In order to do that, each group consists of maximum threestudents will choose a public data set from the following links after consulting with theLecturer.Links to public data set:• KDnuggets• Kaggle• UC Irvine Machine Learning Repository choosing a data set, let’s assume, you have been hired as a data miner / businessanalyst to do a thorough data mining process on the initiative for an organisation. To do thework properly you will need to consider (and do as you see you fit) all the activitiesdescribed in the attached document on the data mining process (make any assumptions ifrequired).Detailed SubmissionRequirementsBusiness case understanding (1,000 words)1. Determine business objectives (300 words)Task: Determine business objectivesThe first objective of the analyst is to thoroughly understand, from a businessperspective, what the client really wants to accomplish. Often the customer has manycompeting objectives and constraints that must be properly balanced. The analyst’s goalis to uncover important factors at the beginning of the project that can influence the finaloutcome. A likely consequence of neglecting this step would be to expend a great dealof effort producing the correct answers to the wrong questions.1.1 Identify the Problem Area (100 words)Identify the problem area (e.g., Marketing, Customer Care, Business Development,etc.). Describe the problem in general terms. Check the current status of the project(e.g., Check if it is already clear within the business unit that we are performing a datamining project or do we need to advertise data mining as a key technology in thebusiness?). Clarify prerequisites of the project (e.g., what is the motivation of theproject? Does the business already use data mining?). Identify target groups for theproject result (e.g., Do we expect a written report for top management or do we expecta running system that is used by naive end users?). Identify the users’ needs andexpectations.Week 7, Friday, 07 May 2021, 11:59 pm via Moodle.1.2 Output: Business objectives (100 words)Describe the customer’s primary objective, from a business perspective, in the datamining project. In addition to the primary business objective, there are typically a largenumber of related business questions that the customer would like to address. Forexample, the primary business goal might be to keep current customers by predictingwhen they are prone to move to a competitor, while secondary business objectives mightbe to determine whether lower fees affect only one particular segment of customers.Informally describe the problem which is supposed to be solved with data mining.Specify all business questions as precisely as possible. Specify any other businessrequirements (e.g., the business does not want to lose any customers). Specifyexpected benefits in business terms.1.3 Output: Business success criteria (100 words)Describe the criteria for a successful or useful outcome to the project from the businesspoint of view. This might be quite specific and readily measurable, such as reduction ofcustomer churn to a certain level or general and subjective such as “give useful insightsinto the relationships.” In the latter case it should be indicated who would make thesubjective judgment. Specify business success criteria (e.g., enrolment rate increasedby 20 percent). Identify who assesses the success criteria. Each of the success criteriashould relate to at least one of the specified business objectives.2. Assess the situation (200 words)2.1 Activities: Inventory of resources (100 words)List the resources available to the project, including: personnel (business and dataexperts, technical support, data mining personnel), data (fixed extracts, access to livewarehoused or operational data), computing resources (hardware platforms), software(data mining tools, other relevant software).2.2 Activities: Sources of data and knowledge (100 words)Identify data sources. Identify type of data sources (on-line sources, experts, writtendocumentation, etc.). Identify knowledge sources. Identify type of knowledge sources(online sources, experts, written documentation, etc.). Check available tools andtechniques. Describe the relevant background knowledge (informally or formally).3. Requirements, assumptions and constraints (250 words)List all requirements of the project including schedule of completion, comprehensibilityand quality of results and security as well as legal issues. As part of this output, makesure that you are allowed to use the data. List the assumptions made by the project.These may be assumptions about the data, which can be checked during data mining,but may also include non-checkable assumptions about the business upon which theproject rests. It is particularly important to list the latter if they form conditions on thevalidity of the results. List the constraints made on the project. These constraintsmight involve lack of resources to carry out some of the tasks in the project within thetimescale required or there may be legal or ethical constraints on the use of the data orthe solution needed to carry out the data mining task.List the risks, that is, events that might occur, impacting schedule, cost or result. Listthe corresponding contingency plans; what action will be taken to avoid or minimizethe impact or recover from the occurrence of the foreseen risks. Identify businessrisks (e.g., competitor comes up with better results first). Identify organisational risks(e.g., department requesting project not having funding for project). Identify financialrisks (e.g., further funding depends on initial data mining results). Identify technicalrisks. Identify other risks that depend on data and data sources (e.g. poor quality andcoverage). Determine conditions under which each risk may occur. Developcontingency plans.4. Determine data mining goals (250 words)4.1 Determine data mining goalsA business goal states objectives in business terminology; a data mining goal statesproject objective in technical terms. For example, the business goal might be “Increasecatalogue sales to existing customers” while a data mining goal might be “Predict howmany widgets a customer will buy, given their purchases over the past three years,relevant demographic information and the price of the item.”Describe the intended outputs of the project that enable the achievement of thebusiness objectives. Note that these are normally technical outputs.Activities: Translate the business questions to data mining goals (e.g., a marketingcampaign requires segmentation of customers in order to decide whom to approach inthis campaign; the level/size of the segments should be specified). Specify data miningproblem type (e.g., classification, description, prediction and clustering). TaskMarks1. Determine business objectives (300 words)22. Assess the situation (200 words)23. Requirements, assumptions and constraints (250 words)64. Determine data mining goals (250 words)5 Misconduct • Engaging someone else to write any part of your assessment for you is classifiedas misconduct.• To avoid being charged with Misconduct, students need to submit their own work.• Remember that this is a Turnitin assignment and plagiarism will be subject to severepenalties.• The AIH misconduct policy and procedure can be read on the AIH website( Submission • Late submission is not permitted, practical submission link will close after 1 hour.Special consideration • Students whose ability to submit or attend an assessment item is affected bysickness, misadventure or other circumstances beyond their control, may beeligible for special consideration. No consideration is given when the condition orevent is unrelated to the student’s performance in a component of the assessment,or when it is considered not to be serious.• Students applying for special consideration must submit the form within 3 days ofthe due date of the assessment item or exam.• The form can be obtained from the AIH website ( or on-campus at Reception.• The request form must be submitted to Student Services. Supporting evidenceshould be attached. For further information please refer to the StudentAssessment Policy and associated Procedure available on( RubricsMarking criteriaHDDCPFULO1: Demonstratebroad understandingofdata mining andbusiness intelligenceand their benefits tobusiness practice.ULO3: Analyseappropriate models andmethods forclassification, prediction,reduction, exploration,affinity analysis, andcustomer segmentationto data miningULO4: Propose a datamining approach usingreal business cases aspart of a businessintelligence strategyReportaddresses allthe tasks.Reportconsists ofno/minormistakes.(13-15 marks)Reportaddresses allthe tasks.Report consistsof a few numberof mistakes.(10-12 marks)Reportaddresses mostof the tasks.Report consistsof a few numberof mistakes.(7-9 marks)Reportaddresses a fewof the tasks.Report consistsof a goodnumber ofmistakes.(5-6 marks)Incompletereport.Unable todeterminebusinessobjectives/situation/ DMactivities/ DMgoals(0-4 marks)


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