The KPMG Data Analytics Virtual Internship is designed to help participants gain practical insight into the work done at KPMG. It offers an opportunity to build career-relevant skills and experience.
Sprocket Central Pty Ltd, a medium-sized bikes and cycling accessories organisation, approached Tony Smith (Partner) in KPMG’s Lighthouse & Innovation Team. Sprocket Central is interested in learning more about KPMG’s capabilities in its Analytics, Information & Modelling team. The project is divided into three main tasks:
Objective: Assessment of data quality and completeness in preparation for analysis.
📂 The client provided KPMG with three datasets:
- Customer Demographic
- Customer Address
- Transactions data (past 3 months)
🔍 We performed preliminary data exploration and identified ways to improve the quality of Sprocket Central’s data.
Objective: Targeting high-value customers based on demographics and customer attributes.
🧭 To build this recommendation:
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We started with a PowerPoint presentation outlining our planned approach.
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The client agreed on a 3-week scope comprising:
- Data Exploration
- Model Development
- Interpretation
🛠️ A detailed plan was prepared to complete the analysis, which included:
- Understanding data distributions
- Feature engineering
- Data transformations
- Modelling
- Results interpretation and reporting
Objective: Use visualisations to present key insights.
📉 A dashboard was developed using Tableau to display data summaries and analysis results.
💼 Key business questions addressed:
- What are the trends in the underlying data?
- Which customer segment has the highest customer value?
- What marketing and growth strategy should Sprocket Central adopt?
- What additional external datasets could provide greater insights into customer preferences and buying behaviour?
Click here to view the certificate
This project simulates a real-world consulting scenario, allowing participants to:
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Conduct end-to-end data analysis.
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Gain experience with industry tools.
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Translate technical findings into business recommendations.