https://github.com/theshashanksinha/deloitte-au
Analyzed telemetry and salary equality data using Tableau and Excel to identify machine downtime patterns and assess gender pay equity, translating raw data into actionable business insights.
https://github.com/theshashanksinha/deloitte-au
data-analytics data-visualization microsoft-excel tableau
Last synced: 3 months ago
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Analyzed telemetry and salary equality data using Tableau and Excel to identify machine downtime patterns and assess gender pay equity, translating raw data into actionable business insights.
- Host: GitHub
- URL: https://github.com/theshashanksinha/deloitte-au
- Owner: theshashanksinha
- Created: 2025-02-25T16:02:58.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-25T16:18:54.000Z (over 1 year ago)
- Last Synced: 2025-02-25T17:27:20.635Z (over 1 year ago)
- Topics: data-analytics, data-visualization, microsoft-excel, tableau
- Homepage:
- Size: 790 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Deloitte Australia Data Analytics Job Simulation
## Overview
This project is part of the **Deloitte Australia Data Analytics Virtual Experience** on Forage. It simulates real-world data analysis tasks, including **factory telemetry analysis** and **forensic salary evaluation**, using **Tableau** and **Excel**.
## Project Tasks
### Task 1: Data Analysis with Tableau
Analyzed telemetry data from four factory locations to determine:
- Which location experienced the highest machine failures
- Which machines had the most downtime
**Key Steps:**
1. Imported JSON telemetry data into **Tableau**
2. Created a **calculated measure** to quantify machine downtime
3. Built **interactive dashboards** with bar charts for downtime per factory and machine type
4. Implemented **filtering functionality** to dynamically analyze specific factory data
### Task 2: Forensic Technology Analysis with Excel
Investigated gender pay equality using an **Equality Score** metric. The goal was to classify job roles into fairness categories.
**Key Steps:**
1. Processed and cleaned salary equality data from an Excel file
2. Created a new column, **Equality Class**, based on predefined thresholds:
- **Fair**: Score between -10 and 10
- **Unfair**: Score below -10 or above 10
- **Highly Discriminative**: Score below -20 or above 20
3. Provided insights into potential pay disparities
## Tools & Technologies
- **Tableau**: Data visualization and dashboard creation
- **Excel**: Data classification and business insights
- **Forage**: Virtual job simulation platform
## Key Takeaways
- Gained hands-on experience with **real-world data analysis challenges**
- Strengthened **data visualization skills** using Tableau
- Applied **data classification techniques** to assess business fairness metrics
- Developed insights into **machine downtime analysis** and **workforce equality**
## How to Explore This Project
1. Download the dataset files from the Forage platform
2. Open **Tableau** and import the JSON telemetry data
3. Follow the outlined steps to recreate the dashboards
4. Open **Excel** and apply conditional logic to classify Equality Scores
## Connect with Me
If you have any feedback or would like to discuss data analytics opportunities, feel free to connect with me on **LinkedIn**!
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### 🚀 Ready to explore real-world data analytics?
Check out the [Deloitte Australia Data Analytics Simulation](https://www.theforage.com/) on Forage.