ICT205 Data Mining Process Applied To Given Data Set Assessment 2 Answer

ICT205 Data Analytics

Assessment 2 – Case Study Team Report and Presentation

Overview

Data Mining process is a manifestation of the best practices which provides a systematic way to conduct data mining projects. There are several steps (i.e., data understanding, data selection, data cleaning, data transformation, model building, testing and evaluation, and deployment) in a typical data mining process. For a successful, it is essential to follow these steps.

Timelines and Expectations

Students are expected to work in a team to prepare a report that details the data mining process on a selected data set. This assessment aims to enable students to create a report that develops their skills to develop data analytics solution for a given case. Students are required to select a data set and answer the following questions:

• What is the purpose of the data set, and what kind of business questions can be answered from the chosen data set?
• Assess the suitability of data preprocessing approaches (e.g., data cleaning, data transformation, data reduction) and justify the applied techniques for the chosen data set.
• Determine and justify the appropriate data mining task and method for the selected data set.
• Build and evaluate multiple models for the selected data set.
• Design an interactive dashboard using 3-4 charts/graphs/illustrations to represent the results.

Case Study Presentation (15%)

10 minutes presentation delivered in-class during the webinar.

Learning Outcomes Assessed

The following course learning outcomes are assessed by completing this assessment task: LO1. review and differentiate between the methods of data analysis and presentation;

LO2. analyse internal and external sources of data relevant to business environments including technology and service utilisation data to identify relationships and trends;

LO3. develop and apply skills in spreadsheets to sort, manage, summarise and display data to support managerial decision-making;

LO4. evaluate conclusions extracted from the various data types and analytic tools;

LO5. demonstrate an ethical approach to gathering, interpreting and applying and presenting business data analytics

Assessment Details

For this assignment, students are required to write 2,500 words report on a specific case study and explain the data mining process applied to a selected data set. Students can choose any suitable data set that is publicly available on the internet.

In week 11, students will be required to present their project and get feedback from the Lecturer to ensure that they are tracking well for their report submission. Students are expected to work in teams of 4 and undergo their own research without collaboration with any other group. No two groups will work on the same case study and students are expected to prepare a comprehensive report on the application of their knowledge of data analytics on a given case study..

1. All reports must include at least 10 academic references which must be done using APA 7 reference style.
2. The case study must assess the value propositions of the chosen data set and discuss what types of business questions can be answered using the data set. It must highlight the suitability of data pre-processing approaches for the selected data set. It must highlight the appropriate data mining task and method that are applicable to the data set. Students must also highlight the best data mining model suitable for the chosen data set.
3. This unit requires you to use APA system of referencing. See Sydney International’s quick reference guide.
4. A passing grade will be awarded to assignments adequately addressing all assessment criteria. Higher grades require better quality and more effort. For example, a minimum is set on the wider reading required. A student reading vastly more than this minimum will be better prepared to discuss the issues in depth and consequently their report is likely to be of a higher quality. So before submitting, please read through the assessment criteria very carefully.

Academic Misconduct

To submit your assessment task, you must indicate that you have read and understood, and comply with, the Sydney International School of Technology and Commerce Academic Integrity and Student Plagiarism policies and procedures.

You must also agree that your work has not been outsourced and is entirely your own except where work quoted is duly acknowledged. Additionally, you must agree that your work has not been submitted for assessment in any other course or program.

Individual report sample structure

• Coversheet (mandatory)
• Title page
• Table of content
• Introduction
• Overview of the data set
• Data Preprocessing
  • Data Cleaning
  • Data Transformation
  • Data Reduction
• Selection and justification of appropriate data mining task and methods
• Modelling
  • Selection of modelling techniques
  • Build models
  • Output Parameter settings
  • Output Model description
  • Evaluate the models
• Conclusions
• References
• Appendix