MySQL, Excel, Tableau Dashboard.
Welcome to the Data Analysis & Visualization Portfolio, featuring three real-world projects that demonstrate the power of data science in solving business, safety, and entertainment challenges. Each project combines exploratory analysis, visualization, and machine learning techniques to generate actionable insights.
📁 1. Netflix Originals Data Analysis: Exploring Trends and Insights
Overview
With the exponential growth of streaming platforms, Netflix has become a leader in original content. This project uses SQL to analyze key trends within Netflix Originals including genres, release dates, runtime, and production countries.
Key Features
SQL-based exploration of Netflix Original metadata.
Analysis of genre distribution over time.
Identification of top producing countries and peak release periods.
Visualization-ready queries to support strategic content planning.
Why It Stands Out
Provides content strategists and entertainment stakeholders with valuable data-backed insights into the evolution of streaming content trends.
📁 2. Road Accident Data Visualization in Tableau
Overview
Road accidents are a global public safety issue. This project develops a Tableau dashboard to visualize accident data, helping stakeholders identify patterns and mitigate risks.
Key Features
Interactive dashboards with filters for time, location, and weather.
Identification of high-risk accident zones.
Analysis of factors contributing to accidents (e.g., vehicle type, time of day).
Why It Stands Out
Empowers policymakers, traffic authorities, and urban planners to make informed decisions that improve road safety.
📁 3. Market Entry Strategy for ABG Motors Using Data Science
Overview
This project supports ABG Motors in exploring market entry into India. It involves comparing consumer behavior in Japan and India and building a predictive model to forecast car purchase likelihood.
Key Features
Exploratory data analysis across Indian and Japanese consumer datasets.
Machine learning classification model built on Japanese data.
Application of the model to Indian data to estimate market potential.
Why It Stands Out
Demonstrates the integration of data science with business strategy and provides real-world decision support for market expansion.
🌟 Project Highlights
Technologies Used: SQL, Python, Pandas, Scikit-learn, Tableau, Jupyter
Skills Demonstrated: Data wrangling, EDA, Machine Learning, Data Visualization, Dashboarding
Tools: MySQL, Tableau Public, scikit-learn, Matplotlib, Seaborn
📂 Repository Structure
#Dataset: csv
#images:
project-name/ ├── data/ │ ├── raw/ │ └── cleaned/ ├── notebooks/ │ ├── EDA.ipynb │ └── model_building.ipynb ├── sql_queries/ │ └── analysis_queries.sql ├── dashboards/ │ └── tableau_visuals.twb ├── reports/ │ └── final_report.pdf ├── README.md └── requirements.txt
🤝 Feedback & Collaboration
Collaboration is welcome! If you have suggestions, improvements, or want to contribute:
Open an issue
Submit a pull request
Connect on LinkedIn or via email (contact in individual project folders)
Together, let's turn data into impactful decisions.