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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.

Assignment-1 Guideline:

Assessment Task 1

Intent

This assessment task addresses the following subject learning objectives (SLOs) : 1 and 2.

Task

In this assignment, students will give a data exploration repor t on their work in the project. Their group will d escribe 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.

Length

15 pages max in an 11 or 12-point font.

Criteria Linkages (Please insert addition rows i n table where required)

Assessment Criteria

Weight (%)

SLO

GA

1

Depth of understanding of the business problem and quality of data exploration results.

100%

1, 2

D, E

2

3

4

5

6

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 analyze 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.

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.
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