MBA522 Business Intelligence Assignment
| Assessment Details and Submission Guidelines | |
| School | School of Business |
| Course Name | Master of Business Analytics |
| Unit Code | MBA522 |
| Unit Title | Business Intelligence |
| Assessment Author | Dr Ken Mardaneh |
| Assessment Type | Assignment [Individual] Report |
| Assessment Title | Assignment 1 |
| Unit Learning Outcomes covered in this assessment | Introduce Business Intelligence (BI) as a broad category of applications and technologies for gathering, storing, analysing and providing access to data to help organisations make better decisions. |
| Weight | 10% |
| Total Marks | 100Marks (this will be converted to 10% of total marks for the unit) |
| Word limit | 1000 |
| Release Date | Week 1 |
| Due Date | Week 3 |
| Submission Guidelines | All work must be submitted on Moodle by the due date along with a completed Assessment Cover Sheet. The assignment must be in MS Word format, 1.5 spacing, 11-pt Calibri (Body) font and 2 cm margins on all four sides of your page with appropriate section headings. Reference sources must be cited in the text of the report, and listed appropriately at the end in a reference list using APA or IEEE referencing style for School of Business and School of Information Technology and Engineering respectively. |
| Extension / Special Consideration | If an extension of time to submit work is required, an Application for Special Consideration and supporting documentation must be submitted online via your Academic Management System (AMS) login: https://online.mit.edu.au/ams. The Application for Special consideration must be submitted no later than three (3) working days after the due date of the specific piece of assessment or the examination for which you are seeking Special Consideration. In the case of serious illness, loss or bereavement, hardship or trauma students may be granted special consideration. |
| Academic Misconduct | Academic Misconduct is a serious offence. Depending on the seriousness of the case, penalties can vary from a written warning or zero marks to exclusion from the course or rescinding the degree. Students should make themselves familiar with the full policy and procedure available at:http://www.mit.edu.au/about-mit/institute-publications/policies-procedures-and-guidelines/Plagiarism-Academic-Misconduct-Policy-Procedure. For further information, please refer to the Academic Integrity Section in your Unit Description. |
Assignment Description
Students are required to produce an individual assignment using data provided. Data is embedded in WEKA/Data and you need to use Credit data as well as Weather data. You need to use Business intelligence theory, concepts, tools and terminology that you have learnt from Weeks 1 to 6to analyse the data and to write upthe assignment.
Credit data is fromamortgage lender company. The business sells categories of products including house mortgages.
The variables for the credit data are as per the table below:
| Variables | Data type |
| 1. Checking-Status | Nominal |
| 2.Duration | Numerical |
| 3. Credit history | Nominal |
| 4. Purpose | Nominal |
| 5.Credit_amount | Numerical |
| 6. Saving_Status | Nominal |
| 7. Employment | Nominal |
| 8. Instalment_commitment | Numerical |
| 9.Personal_status | Nominal |
| 10. other_parties | Nominal |
| 11. residence_since | Numerical |
| 12. Property_magnitude | Nominal |
| 13. age | Numerical |
| 14. Other-payment_plans | Nominal |
| 15. housing | Nominal |
| 16. existing_credits | Numerical |
| 17. Job | Nominal |
| 18. num_dependents | Numerical |
| 19. Own_telephone | Nominal |
| 20. Foreign_worker | Nominal |
| 21. class | Nominal |
Assignment instructions:
The main challenge in the business is to increase sales, revenue and profit. For this reason the company has decided to conduct a business analytics for informed decision making.
Assignment structure:
- Introduction– Introduce the business problems Describe the main objective of the researchers who collected this dataset Describe how you want to achieve this objective in this assignment
- Use credit.arff data Load data Preprocess data Analyse attributes Analyse results
- Use credit.arff data to split the data into train and test set
- credit-test.arff
- Run the test and interpret the results
- Experimenter: Setup Using the data, Cross-validate the experiment Interpret the analysis
- ClassifierUse weather data to pre-process Choose classifiers (Nive Bayes, k-nearest neighbour, decision tree, ensemble including stacking and voting)Run the analysis Interpret the output
- Visualisation of results Visualise the output Interpret the results
- Report writing
Write a report of the assignment that elaborates your findings, analysis, and specifically interpretation of the analysis.
Note: You need to include all the analytics in the word document and as part of your report
Word limit: 1000
Submission: You need to submit both assignment word document, and raff files.
MBA522 Business Intelligence Assignment [Individual] Marking Guide (15 Marks)
| Criteria | Possible Marks% | Marks Allocated |
| Introduction– Introduce the business problems Describe the main objective of the researchers who collected this dataset Describe how you want to achieve this objective in this assignment | 10 | |
| Use credit.arff data Load data Preprocess data Analyse attributes Analyse results | 10 | |
| Experimenter: Setup Using the data, Cross-validate the experiment Interpret the analysis | 10 | |
| ClassifierUse weather data to pre-processChoose a classifierRun the analysisInterpret the output | 10 | |
| Visualisation of resultsVisualise the outputInterpret the results | 10 | |
| Report writing Write a report of the assignment that elaborates your findings, analysis, and specifically interpretation of the analysis. Presentation of the report | 50 | |
| Total | 100% | |
| Overall Comments: Assessor Name: Assessor Signature: | = _____/10__ Marks Date: |