Assignment-1 Guideline:
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Assessment Task 1
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Intent
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This assessment task addresses the following subject learning objectives (SLOs): 1 and 2.
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Task
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In this assignment, students will give a data exploration report on their work in the project. Their group will describe the results of their data exploration and feature engineering by using the SAS Viya tool. The report should cover the business problems, characteristics of the data, and transformation of the data. The report should be structured and presented in line with professional industry report format.
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Length
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15 pages max in an 11 or 12-point font.
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Criteria Linkages (Please insert addition rows in table where required)
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Assessment Criteria
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Weight (%)
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SLO
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GA
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1
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Depth of understanding of the business problem and quality of data exploration results.
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100%
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1, 2
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D, E
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2
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3
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4
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5
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6
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Assessment Task 1: Data Exploration
Objective: The main objective of this assessment task is to apply data exploration and feature engineering techniques to real-world business problems.
Relevant Learning Objectives:
• Subject Learning Objectives: SLO 1
• Course Intended Learning Outcomes: CILO D.1
Format:
• Type: Report
• Work: Group assignment, but each member will be individually assessed.
Weightage: 30% of the overall grade.
Task Description: Students are required to:
1. Form. groups of 2-3 (you may increase group size at max of 5 members based on your tutor’s choice) members.
2. Select a dataset similar with the COMMSDATA (in SAS Viya Course) or any other
existing datasets is available for classification task. Selecting a right dataset is key in this assignment. Please ensure to select a large dataset (over 1000 data points).
3. Select a predictive business analytics task based on the chosen dataset.
4. Collaboratively analyse both the chosen business problem and its associated dataset.
5. Submit a report, detailing:
o The business problem they aim to solve.
o Characteristics of the chosen dataset.
o Data transformation processes applied.
o Proposed method to address the data mining problem.
Additionally, the report should also describe:
• The composition of the group.
• Roles and responsibilities of each team member.
• A proposal for addressing the data mining problem.
• A comprehensive plan outlining how they intend to solve the problem.
Assessment Criteria: Assignments will be evaluated based on:
1. Description of business problem
2. Quality and feasibility of the proposal and plan.
3. Data exploration and initial findings:
- Quality of pre-processing
- Quality of initial findings
4. EDA Visualisation
Submission Details:
• Format: Electronic copy
• Platform. Canvas for report and SAS Viya (in Exchange Folder) for upload the pipeline
• Maximum Length: 15 pages (using 11 or 12-point font)
• Due Date: 11.59pm, Friday 8 September 2023
• Feedback Timeline: Feedback with marks will be provided within 2 to 3 weeks after submission.