💼 Deloitte Data Analytics Simulation – Daikibo Case Study

This repository showcases my completed tasks from the Deloitte Data Analytics Simulation on Forage. The case study focuses on a global manufacturing company, Daikibo, with two main challenges: ensuring fair employee compensation and monitoring machine health across international factories.

I used Excel and Tableau to clean, analyze, and visualize the data — drawing clear business insights and making recommendations, just like in a real analyst role. 📊🔍

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📊 Task 1: Employee Equality Score Classification (Excel)

🔧 What I Did:

• Analyzed employee compensation data from Daikibo's factories in Tokyo, Osaka, Berlin, and Shenzhen.
• Used Excel to classify equality scores into 3 categories:
  • ✅ Fair: -10 to +10
  • ⚠️ Unfair: -11 to -20 or 11 to 20
  • ❌ Highly Discriminative: Less than -20 or greater than 20
• Applied an Excel formula to auto-classify each row, reducing error and ensuring consistency.

📌 Insights I Gained:

• Several job roles in Berlin and Shenzhen had more highly discriminative scores — indicating potential regional policy misalignment.
• Managerial roles showed more fairness than manual labor roles, highlighting a possible systemic bias in lower-tier compensation.

📁 Files:

• Equality Table - Original.xlsx
• Equality Table - Cleaned.xlsx

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🏭 Task 2: Machine Downtime Analysis (Tableau)

🔧 What I Did:

• Analyzed JSON telemetry data from Daikibo’s machines across 4 factories.
• Created a calculated field in Tableau to track unhealthy machine status (10 minutes of downtime per flag).
• Built an interactive dashboard showing:
  • Factory with the highest downtime
  • Most problematic machine types
  • Filtering across factories for deeper drilldown

📌 Insights I Gained:

• Daikibo Factory Meiyo (Tokyo) had the highest total downtime over the month.
• The Type B and Type G machines were consistently underperforming in that factory.
• This suggests those specific machines may need preventive maintenance or vendor review.

📁 Files:

• Dashboard.png
• Down Time per Factory.png
• Down Time per Device Type.png

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🧠 What This Project Taught Me:

• 📌 How to structure real-world business problems into analytical workflows
• 📈 Building clean and meaningful data visualizations using Tableau
• 🧹 Applying consistent logic in Excel for large datasets
• 🎯 Identifying trends and root causes by combining logic + visualization
• ✍️ Communicating insights clearly for business stakeholders

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📜 Certificate

🔗 View my Deloitte Forage Completion Certificate

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📫 Let's Connect!

If you liked this project, feel free to star ⭐ the repo or connect with me!

Thanks for visiting! This project is part of my journey to becoming a well-rounded data analyst with strong technical and business communication skills. 💪📊