• 👋 Hi, I’m @Pradnil Birje
• 📊 Passionate about transforming raw data into actionable insights
• 🛠️ Skilled in Power BI, SQL, Python, Tableau, and Excel
• 📈 Interested in Business Intelligence, Data Visualization, and Analytics
• 🚀 Currently building real-world analytics projects and dashboards
• 🌱 Continuously learning and improving in the tech & analytics field
• 📫 How to reach me www.linkedin.com/in/pradnilbirje24
• 😄 Pronouns: He/Him
📌 Technologies: SQL, MySQL
📊 Analyzed customer behavior, sales trends, and business insights using SQL queries and relational database concepts.
📌 Technologies: Power BI, Excel
📊 Interactive dashboard focused on product performance, sales KPIs, and business intelligence reporting.
📌 Technologies: Python, VS Code, Pandas, Matplotlib, Seaborn, Kaggle Dataset
📊 Performed exploratory data analysis and visualized sales performance trends to uncover actionable insights.
- Built a Customer Churn Analysis Dashboard in Power BI, integrating Excel and MySQL data sources, tracking Churn Rate, Active Customers, and MRR in a unified model.
- Developed a real-time streaming dashboard using Power BI Service + Python API to simulate live business performance monitoring.
- Implemented a churn prediction model (Scikit-learn) using tenure, billing, and behavioral data, flagged 20–30% of customers as high churn risk, enabling proactive retention strategies.
- Applied DAX measures, data transformation, and multi-source integration to deliver accurate, decision-ready insights for business stakeholders.
- Analyzed a 3GB+ traffic accident dataset (7.7M+ records) using Pandas and NumPy, identified accident hotspots, severity trends, and key risk factors via EDA and Folium heatmaps.
- Built a Decision Tree Classifier to predict customer purchase behavior; tuned for optimized accuracy using Scikit-learn.
- Conducted sentiment analysis on social media data using NLP (WordCloud, text preprocessing) to surface brand perception trends.
- Delivered 5 data science projects covering EDA, ML, and visualization, demonstrating the ability to handle large-scale, real-world datasets independently.
• 🎓 Master In Data Science & Analytics With Artificial Intelligence - NSDC
• 📊 Python for Data Science - IBM
• 💻 Analyzing and Visualizing Data with Microsoft Power BI - Itvedant
Understanding the key differences between Data Analysis and Data Analytics, including roles, processes, tools, and business impact.
⭐️ From PradnilBirje
📊 Turning Data into Meaningful Insights
“Without data, you're just another person with an opinion.”