Assessment details Assessment 1: Case Studies & Presentation Overview Weight Length Due date ULO 10% 3-6 Minutes Video Presentation Session 6 1, 2, 3 Introduction This assessment item relates to the unit learning outcomes as in the unit descriptor. Objective of this case study to assess the ability of students to understand large data sets and apply their knowledge in analytics to come up with useful insights. This assessment is designed to improve student presentation skills and to give students experience in researching a topic and presenting a report relevant to the Unit of Study subject matter. Task 1. Find a data set from an open data website Example: https://data.gov.au/ https://www.springboard.com/blog/free-public-data-sets-data-science-project/ https://www.dataquest.io/blog/free-datasets-for-projects/ https://www.kaggle.com/datasets The data source should be large enough (at least 10 columns and 250 rows). 2. Present your insights including some basic analytics and at least five different visualisations.
3. This is now an individual assignment, not a group assignment. 4. You need to record your presentation, 3-6 minutes. You and your slides should be clear in the video file. 5. Submit your video file of your presentation in the provided link by the due date. Only original file will be accepted; a link to your video file will not be marked. Submission Instructions All submissions are to be submitted through the Moodle. It is your responsibility to upload a quality and standard format file in the Moodle. The link for video will not be accepted and will not be marked. Submissions must be made by the due date and time (which will be in the session detailed above) and determined by your Unit coordinator. Submissions made after the due date and time will be penalized at the rate of 10% per day (including weekend days).
Assessment 2: Research Study Overview Weight Length Due date ULO 10% 1500 Session 9 3, 4, 5 Introduction This assessment item relates to the unit learning outcomes as in the unit descriptor. This assessment is designed to improve student research skills and to give students experience in researching a topic and writing a report relevant to the Unit of Study subject matter. Task Perform a literature review on a known topic in business analytics. It can be any topic on tools, methodologies or applications. Some examples include, but not limited to: • Use of predictive analysis in healthcare industry • Comparison of BI tools • Techniques of predictive analysis • Methods of representing multi-dimensional data in visualisations • Analytics techniques to improve logistics management • Security of data and privacy concerns in analytics Please note that this is an individual project. Discuss with your lecturer before week 7 to decide on a topic. The topic needs to be chosen before week 7. Based on your review you need to submit a report in IEEE format; see the word file in the Moodle. Submit your report in a word or pdf format. Your report should be limited to 1200-1500 words. The paper you select must be directly relevant to one of the above topics or another topic and
be related to Data Science. The paper must be approved by your lecturer and be related to what we are studying this semester in Business Analytics. The paper can be from any academic conference or other relevant Journal or online sources such as Google Scholar, or Academic department repositories. All students must select a different paper. Thus, the paper must be approved by your lecturer before proceeding. Discuss with your lecturer before week 7 to decide on a topic. The topic needs to be chosen before week 7. In case two students are wanting to present on the same paper, the first who emails the lecturer with their choice will be allocated that paper. Please note that popular magazine or web-site articles are not academic papers. The paper you chose should be published in the last 5 years. our report should be limited to approx. 1500 words (not including references). Though your paper will largely be based on the chosen article, you may use other sources to support your discussion or the chosen papers premises. Citation of sources must be in the IEEE style. Based on your review you need to submit a report in IEEE format; see the word file in the Moodle. Report Content Title Page: The title of the assessment, the name of the paper you are reporting on and its authors, and your name and student ID. Introduction: Identification of the paper you are critiquing/ reviewing, a statement of the purpose for your report and a brief outline of how you will discuss the selected article (one or two paragraphs). Body of Report: Describe the intention and content of the article. Document a critical analysis regarding business case, brief overview of the dataset, data type, variables and their relationships. You may assume such details of dataset if not considered in your chosen paper. Moreover, critically describe the adopted business analytics models and decision-making tools which has been used and applied in your chosen paper. In addition to that, report the outcomes of the recommend business directions. If such recommendation is not outlined in your chosen paper, discuss and justify your own view. Conclusion: A summary of the points you have made in the body of the paper. The conclusion should not introduce any ‘new’ material that was not discussed in the body of the paper. (One or two paragraphs) References: A list of sources used in your text. They should be listed alphabetically by (first) author’s family name. Follow the IEEE style. The footer must include your name, student ID, and page number. Note: reports submitted on papers which are not approved or not the approved paper registered for the student will not be graded and attract a zero (0) grade. Submission Instructions All submissions are to be submitted through turn-it-in. Drop-boxes linked to turn-it-in will be set up in the Unit of Study Moodle account. Assignments not submitted through these drop-boxes will not be considered
Assessment 3: Assignment Overview Weight Length Due date ULO 30% 2000-2500 Session12 4, 5 Introduction This assessment item relates to the unit learning outcomes as in the unit descriptor. This assessment is designed to improve student analytic skills and to give students experience in problem solving in business analytics. Task Answer the assignment questions given in the Moodle and upload a word file. To answer question one, you will need to refer the provided insights report which is also given in the Moodle. This is an individual task. Submission Instructions All submissions are to be submitted through turn-it-in. Drop-boxes linked to turn-it-in will be set up in the Unit of Study Moodle account. Assignments not submitted through these drop-boxes will not be considered. Submissions must be made by the due date and time (which will be in the session detailed above) and determined by your Unit coordinator. Submissions made after the due date and time will be penalized at the rate of 10% per day (including weekend days). The turn-it-in similarity score will be used in determining the level if any of plagiarism. Turn-it-in will check conference websites, Journal articles, the Web and your own class member submissions for plagiarism. You can see your turn-it-in similarity score when you submit your assignment to the appropriate drop-box. If this is a concern you will have a chance to change your assignment and re-submit. However, re-submission is only allowed prior to the submission due date and time. After the due date and time have elapsed you cannot make re-submissions and you will have to live with the similarity score as there will be no chance for changing. Thus, plan early and submit early to take advantage of this feature. You can make multiple submissions, but please remember we only see the last submission, and the date and time you submitted will be taken from that submission. Your report should be a single word or pdf document containing your report.
The purpose of assessment is to assess students on the following Learning Outcomes: LO1: Analyse the growth of big data and need for a scalable processing framework. Synthesize the fundamental characteristics, storage, analysis techniques and the relevant distributions. LO2: Expertly apply techniques to perform big data query manipulation, evaluate various data storage option and type of aggregated data modelling. Through a critical study, choose an appropriate storage model based on the application requirements for processing large amounts of structured and unstructured data. Objective In this assessment you will have to research a small case study and you will need to apply your knowledge to identify the main issues, prioritise, provide insights and to discuss alternatives. You must write a Case Study Report about your company discussing the strategic plan of an organization. To present a case study based on the selected organization’s current analytics strategy and your recommended strategy. Identify a key business initiative for your organization, something the business is trying to accomplish over the next 9 to 12 months. It might be something like improve customer retention, optimize customer acquisition, reduce customer churn, optimize predictive maintenance, reduce revenue theft, and so on. Brainstorm and write down what (1) customer, (2) product, and (3) operational insights your organization would like to uncover in order to support the targeted business initiative. Start by capturing the different types of descriptive, predictive, and prescriptive questions you’d like to answer about the targeted business initiative. Tip: Don’t worry about whether or not you have the data sources you need to derive the insights you want (yet).
Write down data sources that might be useful in uncovering those key insights. Look both internally and externally for interesting data sources that might be useful. Tip: Think outside the box and imagine that you could access any data source in the world. Be analytical within your report and examine key terms and theoretical relationships in depth. General Instructions 1. Your writing should be clear and concise and be in your own words. 2. The Case Study report should be written in appropriate business language so that your analysis and discussion have an objective tone. 3. Use headings to guide the reader and include tables or diagrams that make the case clearer. 4. The Case Study report must be in the range of 1,500-2,500 words in length excluding references. 5. The referencing style must follow the IEEE referencing style. Submission Guidelines 1. Follow the links in Moodle to upload your report on or before the deadline. The report must be submitted on the LMS in the respective link i.e. MITS6005 Case Study- (Melbourne/Sydney) 2. A document that consists of introduction to the problem that you are working on with strategic plan and the resources that might help in the analysis should be mentioned. 3. Late penalty applies on late submission, 10% per day would be deducted. 4. Incidence of plagiarism will be penalized.