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Deloitte Data Analytics is a virtual internship programme in which we will be using Tableau and Excel to analyze operational and HR datasets to uncover machine downtime patterns and pay equity insights.

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💼Deloitte Data Analytics Simulation

Role: Data Analyst

Tools Used: Tableau, Excel

Skills Applied: Data Cleaning · Exploratory Analysis · Data Visualization · Business Logic Design

📌 Project Overview

In this project, I am a Data Analyst working with two real-world datasets focused on manufacturing operations and gender pay equality. The goal was to extract actionable insights using data analysis and visualization — assisting business stakeholders in understanding risks, performance gaps and compliance issues.

I used Excel for forensic-style classification and Tableau for building an interactive dashboard that supports executive decision-making.

🧩 Tasks & Deliverables

🔧 Task 1: Machine Downtime Analysis using Tableau

Objective Identify operational inefficiencies and high-risk machines from factory machine telemetry.

What I did:

  • Analyzed machine health metrics across multiple factories

  • Created a custom calculated field to classify machines as “Unhealthy” or “Healthy”

  • Designed bar charts and filters to compare breakdown frequency across locations

  • Highlighted Factory A as the most failure-prone site and pinpointed specific machines causing repeated downtime

  • Delivered an interactive Tableau dashboard to allow factory managers to explore downtime trends by machine and location

🔍 Key Insight: Factory A had the highest breakdown count, with certain machines contributing disproportionately — a signal for preventive maintenance.

⚖️ Task 2: Gender Pay Equality Classification in Excel

Objective: Evaluate salary fairness across genders and flag discriminatory pay structures.

What I did:

  • Cleaned and normalized the raw employee salary dataset

  • Applied logical rules to compute pay gap thresholds

  • Created a new column Equality Class with three distinct labels:

    • Fair (minimal pay gap)

    • Unfair (moderate discrepancy)

    • Highly Discriminative (large or systemic gap)

  • Used conditional formatting to visually distinguish records and enhance interpretability

  • Delivered a well-structured, business-ready Excel sheet for HR decision-makers

🔍 Key Insight: Several roles, particularly in mid-level technical and operational categories, showed systematic underpayment of one gender — actionable for HR.

📊 DASHBOARD

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✅ Key Outcomes

  • Developed a decision-ready Tableau dashboard for manufacturing insights

  • Delivered an Excel-based forensic pay analysis tool for HR review

  • Demonstrated the ability to work across domains — operations and HR analytics

  • Strengthened my skills in business problem-solving, not just technical execution

🛠️ Tools & Skills Used

📊 Data Analysis

📗 Excel Spreadsheets — Data preprocessing, Computing

📈 Tableau — Interactive dashboards

🧹 Data Cleaning — Missing values, duplicates

🎯 KPI Design — Created summary insights

✨ Why This Project Matters

This project demonstrates how I, as a data analyst, translate business questions into structured insights using the right tools. It shows:

  • A solid grasp of data-driven problem-solving

  • Attention to both technical detail and stakeholder expectations

  • Proficiency in Tableau and Excel for two very different use cases

  • Strong foundations in ethical analytics — including bias detection and fairness analysis

Project by: Mallika Uppuganti

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Deloitte Data Analytics is a virtual internship programme in which we will be using Tableau and Excel to analyze operational and HR datasets to uncover machine downtime patterns and pay equity insights.

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