📊 Data Analytics Portfolio Author: Sai Ashok Education: Computer Science Engineering @ Bangalore Institute of Technology Career Goal: Aspiring Data Analyst

📌 About This Repository This repository serves as my portfolio, showcasing my journey into data analytics through hands-on projects. Each project is designed to highlight key data skills such as cleaning, visualization, analysis, and predictive modeling.

🛠️ Skills & Tools Programming: SQL , Python (Pandas, NumPy, Matplotlib, Seaborn) Data Visualization: Tableau, Power BI, Matplotlib, Seaborn Data Processing: Excel, Pandas, SQL

📂 Projects

1️⃣ Project Name - covid 19 analysis Tools Used: SQL, Python, Tableau

• Cleaned and transformed raw data
• Performed exploratory data analysis (EDA) to find key insights
• Built interactive dashboards for business decision-making
• check it out ! https://public.tableau.com/app/profile/saiashok.karadi/viz/coviddashboard_17405063384210/Dashboard1

2️⃣ Project Name - data_cleaning
Tools Used: SQL, Python

• Cleaned and transformed the nashville_housing dataset to improve data consistency.
• Converted data types, standardized values, and populated missing address fields.
• Split address-related columns (PropertyAddress) into separate fields.
• Replaced categorical values (e.g., "Y"/"N" → "Yes"/"No") for better readability.
• Removed duplicate records using ROW_NUMBER() and deleted unused columns.
• Performed exploratory data analysis (EDA) to uncover key insights.🚀

3️⃣ Project Name - Movies Correlation

Tools Used: Python (Pandas, NumPy, Matplotlib, Seaborn)

• Imported and processed movie dataset using libraries like Pandas and NumPy.
• Converted column data types (e.g., changing object types to numeric for analysis).
• Identified and removed duplicate records to ensure data accuracy.
• Created scatter plots to visualize relationships between key variables (e.g., budget vs. revenue).
• Analyzed trends to understand patterns in movie performance.
• Built a correlation table using a heatmap to identify strong relationships between features.
• Derived insights on factors influencing movie success using data visualization. 🚀

4️⃣ Project Name - Layoff Data Analysis

Tools Used: MySQL (CTEs, Window Functions, Aggregations)

• Imported and processed layoff dataset using SQL queries.
• Created staging tables and applied row numbering to remove duplicate records.
• Standardized data fields (e.g., trimming company names, unifying industry labels).
• Handled missing values by cross-referencing related records.
• Performed exploratory data analysis to identify trends in layoffs by company, industry, country, and year.
• Used window functions to calculate rolling totals and rank top companies by layoffs.
• Extracted key insights into workforce reductions across different sectors and time periods. 🚀

How to Use This Repository

1. Clone this repository: git clone https://github.com/saiashok0981/portfolioproject.git
2. Explore individual project folders, each containing SQL scripts, and dashboards.

📬 Connect with Me

• LinkedIn: https://www.linkedin.com/in/sai-ashok-60b394251/
• Email: saiashok103@gmail.com