776 – Business analysts.

You are required to complete the entire COMP30026 Business Intelligence and Analytics case study professionally and in full, using the following Kaggle dataset as the primary data source:

This dataset contains car sales information such as selling prices, brands, models, transmission types, mileage, colors, body types, and regional details. It is suitable for building a comprehensive Business Intelligence and Predictive Analytics solution.

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1. PROJECT OBJECTIVE

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Develop a complete Business Intelligence and Analytics solution for AutoSphere Oman, a fictional automotive company operating across Oman. The goal is to analyze vehicle sales data and use dashboards and predictive analytics to support strategic business decisions.

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2. REQUIRED DELIVERABLES

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Please prepare and submit the following files:

1. Report in Microsoft Word (.docx)

2. Report in PDF format (.pdf)

3. Power BI dashboard file (.pbix)

4. Cleaned dataset in Excel (.xlsx)

5. Cleaned dataset in CSV (.csv)

6. PowerPoint presentation (.pptx)

7. Final organized project folder containing all deliverables

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3. REPORT REQUIREMENTS

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– Minimum 2,000 words

– Written in professional academic English

– Font: Calibri, Size 12

– Headings: Font Size 14, Bold, and Underlined

– Referencing Style: APA 7th Edition

The report must include:

– Title Page

– Table of Contents

– List of Figures

– List of Tables

– Page Numbers

– References

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4. REPORT STRUCTURE

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1. Introduction

2. Existing Business Process and Problem Statement

3. Comparative Study of Two Real BI Implementations

4. Data Collection and Data Analysis

5. Proposed Business Intelligence Framework

6. CostBenefit and ROI Analysis

7. Challenges and Recommendations

8. Conclusion

9. References

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5. SECTION DETAILS

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1. Introduction

– Introduce AutoSphere Oman and its business operations.

– Explain the importance of Business Intelligence and Analytics.

– State the objectives of the project.

– Briefly describe the dataset used.

2. Existing Business Process and Problem Statement

– Describe the current fragmented systems.

– Explain issues in sales, inventory, service, and marketing.

– Present an As-Is Process Diagram.

3. Comparative Study

– Compare two companies that successfully use BI:

– Toyota Motor Corporation

– Tesla, Inc.

– Discuss:

– Data Governance

– Ethical Analytics

– Privacy and Security

– Include a comparison table.

4. Data Collection and Data Analysis

– Download and clean the Kaggle dataset.

– Explain all important columns.

– Perform exploratory data analysis.

– Create at least four dashboards.

– Develop a predictive analytics dashboard to forecast future sales.

5. Proposed Business Intelligence Framework

– Design a complete BI architecture including:

– Data Sources

– ETL Process

– Data Warehouse

– Analytics Layer

– Dashboards

– End Users

6. CostBenefit and ROI Analysis

– Estimate implementation costs and expected benefits.

– Calculate ROI using:

ROI = ((Benefits – Costs) / Costs) 100

7. Challenges and Recommendations

– Discuss implementation barriers and risks.

– Provide practical recommendations.

8. Conclusion

– Summarize the overall findings and expected business impact.

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6. DATA CLEANING REQUIREMENTS

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Perform full data preparation, including:

– Removing duplicates

– Handling missing values

– Correcting inconsistent data

– Converting data types

– Treating outliers where necessary

Document all cleaning steps in the report.

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7. POWER BI REQUIREMENTS

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Create the following DAX measures:

– Total Revenue

– Total Units Sold

– Average Selling Price

– Total Brands

– Total Models

– Forecasted Sales

– Customer Retention Proxy

– Inventory Turnover Proxy

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8. REQUIRED DASHBOARDS

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Dashboard 1: Executive Sales Overview

– Total Revenue

– Total Units Sold

– Average Selling Price

– Monthly Sales Trend

– Top 10 Brands

– Sales by Region

Dashboard 2: Product and Inventory Analysis

– Best-Selling Models

– Sales by Body Type

– Transmission Analysis

– Color Preferences

Dashboard 3: Customer and Service Insights

– Simulated Customer Retention Rate

– Delayed Service Customers

– Customer Segmentation

Dashboard 4: Predictive Analytics Dashboard

– Sales Forecast for the Next 12 Months

– Trend Analysis

– Confidence Intervals

Dashboard 5 (Optional for Higher Quality): ROI Dashboard

– Estimated Savings

– ROI Percentage

– Payback Period

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9. PREDICTIVE ANALYTICS

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Use Power BI Forecasting or a time series model to predict vehicle sales for the next 12 months.

Provide:

– Forecast chart

– Interpretation of results

– Strategic recommendations

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10. POWERPOINT PRESENTATION

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Prepare a professional presentation with 12 to 15 slides.

Suggested Slide Structure:

1. Title Slide

2. Company Background

3. Problem Statement

4. Comparative Study

5. Dataset Overview

6. Data Cleaning Process

7. Dashboard 1

8. Dashboard 2

9. Dashboard 3

10. Predictive Analytics Dashboard

11. Proposed BI Framework

12. ROI Analysis

13. Challenges

14. Recommendations

15. Conclusion

Include screenshots from Power BI.

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11. EXPECTED BUSINESS INSIGHTS

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The analysis should identify:

– Highest-performing brands

– Best-selling vehicle models

– Regional sales differences

– Forecasted future sales

– Opportunities to improve inventory allocation

– Opportunities to increase customer retention

– Financial viability of the BI solution

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12. FINAL PROJECT FOLDER STRUCTURE

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COMP30026_AutoSphere_Oman/

Report.docx

Report.pdf

Presentation.pptx

AutoSphere_BI_Dashboard.pbix

Cleaned_Car_Sales_Data.xlsx

Cleaned_Car_Sales_Data.csv

References/

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13. QUALITY REQUIREMENTS

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The completed project must:

– Be academically rigorous and professionally written

– Be free from grammar and formatting errors

– Include relevant tables, charts, and diagrams

– Fully satisfy all case study requirements

– Be ready for submission and presentation

– Be of a quality suitable for achieving full marks

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14. IMPORTANT NOTES

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– Use only the specified Kaggle dataset.

– Adapt all findings to the AutoSphere Oman case study.

– Ensure all source files remain editable.

– Verify that all Power BI visuals and calculations work correctly.

– Deliver the project as a complete and organized package ready for submission.

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