Nibedita Sahu

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About Me

I'm Nibedita, a Data Science & Analytics Enthusiast with a strong foundation in Mathematics. I specialize in using Python, SQL, Power BI, Excel, and Business Mathematics and Statistics to analyze, visualize, and interpret data. With a passion for Problem-Solving and Data Storytelling, I focus on making complex data easy to understand through clear insights and visualizations. I'm constantly learning and refining my existing skills, working on projects that challenge me to grow and explore new opportunities.



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Skills

Tools & Technologies

Programming Languages: Python SQL

Libraries: NumPy Pandas Matplotlib Seaborn

Data Management & Reporting: Power BI Excel

Development Environments: Jupyter Notebook VS Code Google Colab

Reporting & Designing: PowerPoint Canva

Techniques & Concepts
Data Collection Data Cleaning Data Preprocessing Data Integration Exploratory Data Analysis (EDA) Descriptive Statistics Correlation Analysis Outlier Detection Trend Analysis Business Mathematics Probability Theory Statistical Analysis Feature Engineering Time Series Analysis Data Visualization Data Profiling Dashboard Development KPI Identification Data Storytelling Business Understanding Analytical Thinking Problem Solving

Background

🎓 Bachelor of Science in Mathematics

With a strong analytical mindset shaped through my academic journey, I've developed a natural inclination toward solving data-driven problems. My degree has helped me understand the logic, structure, and patterns that form the backbone of Data Science & Analytics.

Projects

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Electric Vehicle Population Analysis

A complete end-to-end data analysis project exploring Electric Vehicle adoption. Used SQL, Python, and Power BI to clean, analyze, and visualize trends in EV types, range, and policy eligibility. Delivered actionable insights on top-performing models, regional adoption, and CAFV alignment through a multi-page report and presentation.

GitHub
Jupyter Notebook SQL Script
Static Report Interactive Report Presentation

IBM HR Employee Attrition Analysis

This project analyzes employee turnover using Python and Power BI to find out why employees leave. It explores factors like job roles, departments, and employee demographics to identify patterns and trends. The insights help HR teams make better decisions to improve employee retention. Visualizations and data-driven analysis make it easy to understand key factors affecting attrition.

GitHub View Notebook
Static Report Interactive Report
Project 4 Image
Project 3 Image

Customer Sales Performance Analysis

An end-to-end data analytics project analyzing customer sales using Python, SQL, and Power BI. Data was explored and cleaned in Jupyter Notebook, queried with MySQL, and visualized through interactive Power BI dashboards to enable clear identification of sales trends, customer behaviors, and key business drivers.

GitHub
Jupyter Notebook SQL Script
View Presentation

Credit Card Financial Analysis

A Power BI dashboard providing real-time insights into credit card transactions, customer behavior, and key financial metrics. The project leverages data visualization to identify spending patterns, detect anomalies, and support strategic financial decisions. It combines analytical rigor with intuitive design for effective data storytelling.

GitHub
Static Report Interactive Report
View Presentation
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Project 1 Image

Super Store Sales Analysis & Forecasting

An interactive Power BI dashboard designed to analyze superstore sales data, track key performance indicators, and uncover actionable business insights. Leveraging time series analysis, the project provides accurate 15-day sales forecasts to support proactive decision-making. Explore sales trends, product performance, and regional patterns through intuitive visualizations and advanced analytics.

GitHub
Static Report Interactive Report
View Presentation
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