📊 Data Careers Survey Analysis
🧠 Project Overview
This project explores insights from a professional survey focused on "data-related careers" — including roles such as "Data Analyst, Data Engineer, Data Scientist, and Database Developer" — across multiple industries such as "Technology, Finance, and Healthcare".
The goal was to clean, organize, and analyze the dataset to derive insight's such as "work-life balance, salary distribution, satisfaction levels, career entry difficulty" and other key metrics. All analysis, visualization, and reporting were completed in Microsoft Excel.
🎯 Objectives
1 Clean and structure a raw dataset containing survey responses on data careers. 2 Explore cross-industry variations in job satisfaction, work-life balance, and salary. 3 Identify trends in how professionals perceive entry difficulty and career progression. 4 Build an interactive Excel dashboard to communicate key insights visually.
🧰 Tools & Techniques
- Microsoft Excel
. Data Cleaning & Transformation . Pivot Tables & Charts . Conditional Formatting . Dashboard Design & Layout 2. Analytical Skills
. Descriptive Statistics . Comparative & Trend Analysis . Insight Communication
🧹 Data Cleaning Process
The dataset was thoroughly cleaned and validated to ensure accuracy and consistency:
- Removed duplicates and corrected inconsistent values.
- Standardized role titles, industry names, and response categories.
- Handled missing or incomplete entries logically.
- Created derived metrics (e.g., average satisfaction score, salary bracket categories).
- Validated the dataset for dashboard integration.
📊 Dashboard & Report Design
The Excel file includes four major components:
1 Raw Data Sheet: Original dataset before transformation. 2 Cleaned Data Sheet: Structured and standardized dataset for analysis. 3 Report Sheet: Contains all pivot tables and supporting charts. 4 Dashboard Sheet: A visually interactive dashboard summarizing the main findings.
📈 Key Insights
Here are a few insights derived from the analysis:
1 📌 Tech and Finance sectors recorded the highest average salaries among data professionals. 2 🌍 Work-life balance was rated higher in Healthcare and Education compared to Tech. 3 📊 Entry difficulty was rated "Neither Easy nor Difficult" by more 30% of the individuals. 4 💡 Job satisfaction correlated strongly with salary range and perceived career growth opportunities.
📂 Repository Structure
📁 visuals/ — charts and screenshots of the dashboard
📄 Data Career Insights.xlsx — main Excel file with analysis, dashboard, Raw Dataset & Cleaned Dataset
📄 README.md — project overview and documentation
🚀 Results
This project demonstrates my ability to:
- Clean and analyze real-world survey data using Excel.
- Derive actionable insights on workforce and career trends.
- Design an engaging dashboard that communicates findings effectively.
It also reflects my growing expertise in data storytelling, business analytics and insight's visualization.
📬 Contact
Name: Onagadanalyst Role: Data & Market Analyst | Building Expertise in Augmented Analytics and AI Automation LinkedIn: GitHub: https://github.com/o-danalyst Email: onagatheanalyst@gmail.com