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📊 Data Analytics & Visualization Projects

Welcome to my Data Analytics Projects Repository.
This repository contains multiple end-to-end projects focused on data analysis, visualization, and business insights using tools such as Power BI, Python, SQL, and Excel.

Each project demonstrates real-world data analysis workflows including data cleaning, modeling, visualization, and insight generation.


📁 Projects Included

1️⃣ ATM Transactions Analysis

An interactive Power BI dashboard analyzing ATM transaction patterns across different cities and states in India.

🔍 Key Highlights

  • Interactive dashboard built with Power BI
  • Analysis of ATM usage patterns
  • Identification of high-load ATM locations
  • Evaluation of profitability and operational costs

📈 Insights Generated

  • Some regions have high transactions despite fewer ATMs
  • Certain ATMs generate higher revenue through financial transactions
  • Loss-making ATMs identified through margin analysis
  • Profit distribution follows the Pareto Principle (80/20 rule)

🛠 Tools Used

  • Power BI
  • Excel
  • DAX
  • Data Visualization

📂 Project Folder: ATM_Transactions_Analysis


2️⃣ Super Store Sales Dashboard & Forecast

A Power BI sales analytics project analyzing a retail store dataset and forecasting future sales trends.

🔍 Key Highlights

  • Sales performance analysis across regions, categories, and segments
  • Interactive visualizations for business insights
  • Time series forecasting for sales planning
  • KPI monitoring for sales, profit, and quantity

📈 Business Insights

  • Consumer segment generates the largest revenue share
  • California leads in total sales
  • Online payment methods are increasingly preferred
  • Office Supplies is the top performing category

🛠 Tools Used

  • Power BI
  • Data Modeling
  • Business Analytics
  • Time Series Forecasting

📂 Project Folder: SuperStore_Sales_Dashboard


3️⃣ Movie Dataset Analysis & Visualization

A Python data analysis project exploring trends in a movie dataset containing information on nearly 10,000 movies.

🔍 Key Highlights

  • Data cleaning and preprocessing
  • Genre-based movie analysis
  • Popularity and voting trend analysis
  • Visualization of movie trends over time

📊 Analysis Performed

  • Genre distribution analysis
  • Popularity trends
  • Vote count comparisons
  • Year-wise movie release analysis
  • Identification of most and least popular movies

🛠 Tools Used

  • Python
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Jupyter Notebook

📂 Project Folder: Movie_Dataset_Analysis


🛠 Technologies Used

  • Python
  • Power BI
  • SQL
  • Excel
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Data Analysis
  • Machine Learning

📊 Skills Demonstrated

  • Data Cleaning & Preprocessing
  • Exploratory Data Analysis (EDA)
  • Data Visualization
  • Business Intelligence
  • Dashboard Development
  • Statistical Analysis
  • Data Storytelling

👨‍💻 Author

Sameer Shukla

Aspiring Data Scientist & Data Analyst passionate about transforming raw data into actionable insights.


📬 Connect With Me


📄 License

MIT License
Copyright (c) 2025 Sameer Shukla

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