DATA ANALYTICS PORTFOLIO

This repository contains data analytics projects focused on data collection, data cleaning, exploratory analysis, visualization, SQL reporting, dashboard development, and insight generation. The projects demonstrate end-to-end analytics workflows using Python, SQL, Tableau, and reporting tools across real-world datasets.

📌 Project Highlights

Project	Domain	Tools	Dataset Size	Key Output
Rental Property Market Analysis	Real Estate Analytics	Python, Selenium, BeautifulSoup, Pandas, Matplotlib, Seaborn	2,478 rows x 10 columns	Rental market analysis with scraped property listings, data wrangling, EDA, and housing trend insights
Job Market Analysis	Workforce Analytics	Python, Pandas, NumPy, Matplotlib, Seaborn, JSON	1,615,940 rows x 23 columns	Large-scale job posting analysis covering sectors, roles, companies, hiring trends, and skill patterns
Restaurant Market Health Violations	Public Health Analytics	SQL Server, Star Schema, Tableau, Reporting Services	313,676 rows x 17 columns	Data warehouse schema, SQL reporting, Tableau dashboard, and violation trend analysis

📊 Dataset Sources

Project	Dataset	Source	Key Features
Rental Property Market Analysis	NoBroker Rental Listings	Web Scraped Dataset	Rent, deposit, area, maintenance, furnishing, property type, preferred tenants, availability, location
Job Market Analysis	Job Description Dataset	Kaggle	Job titles, roles, company details, sectors, skills, responsibilities, experience, qualifications, salary, work type, portal
Restaurant Market Health Violations	LA Restaurant & Market Health Data	Kaggle	Violation codes, facility details, inspection dates, violation status, program elements, grades, scores, service types

Large external datasets are not included in this repository due to file size and source management considerations. Dataset download instructions are provided inside the respective project data folders.

📂 Repository Structure

data-analytics/
├── README.md
├── requirements.txt
├── .gitignore
├── rental-property-market-analysis/
│   ├── rental_property_market_analysis.ipynb
│   ├── data/
│   │   └── rental_property_listings.csv
│   └── documents/
│       └── rental_property_market_analysis_report.pdf
├── job-market-analysis/
│   ├── job_market_analysis.ipynb
│   └── data/
│       └── README.md
└── restaurant-market-health-violations/
    ├── assets/
    │   ├── restaurant_market_health_violations_dashboard.png
    │   └── star_schema.png
    ├── data/
    │   └── README.md
    ├── diagrams/
    │   └── star_schema.drawio
    ├── documents/
    │   ├── restaurant_market_health_violations_report.pdf
    │   └── restaurant_market_health_violations_presentation.pdf
    ├── reports/
    │   ├── cases_by_program_element.pdf
    │   ├── ratio_by_services.pdf
    │   ├── tabular_report.pdf
    │   └── trend_of_health_violation.pdf
    └── sql/
        └── restaurant_market_health_violations_schema.sql

🧩 Skills Demonstrated

• Data collection and data preparation
• Web scraping with Selenium and BeautifulSoup
• Data cleaning and transformation
• Exploratory data analysis
• Data visualization and reporting
• Large-scale dataset analysis
• JSON parsing and feature extraction
• SQL database design
• Star schema modeling
• Dimensional data warehousing
• Tableau dashboard development
• SQL reporting and PDF report generation
• Analytical interpretation and insight generation

💻 Technology Stack

• Python
• Jupyter Notebook
• Pandas
• NumPy
• Matplotlib
• Seaborn
• BeautifulSoup
• Selenium
• lxml
• JSON
• SQL Server
• Tableau
• Reporting Services

📚 Project Summaries

Rental Property Market Analysis

This project analyzes rental property listings collected from NoBroker.com. The workflow includes web scraping, data cleaning, preprocessing, exploratory data analysis, and visualization.

The analysis focuses on rent, deposit, area, maintenance, furnishing type, property type, preferred tenants, availability, and location. Key findings highlight differences between furnished and unfurnished properties, variation across prime localities, and the relationship between rent and deposit.

Job Market Analysis

This project analyzes a large-scale job posting dataset from Kaggle covering job descriptions across multiple sectors and roles. The workflow includes data cleaning, column reduction, datatype correction, missing-value handling, JSON parsing, exploratory analysis, and visualization.

The analysis explores hiring trends, sector-level demand, role distribution, and job requirement patterns. The cleaned dataset structure supports deeper analysis of job market behavior and employment trends over time.

Restaurant Market Health Violations

This project analyzes LA restaurant and market health violation data using SQL, dimensional modeling, reporting, and dashboard visualization. The workflow includes SQL Server database design, landing table creation, star schema modeling, fact and dimension table design, SQL reporting, and Tableau dashboard development.

The project includes a star schema model, SQL schema script, Tableau dashboard screenshot, reporting outputs, and presentation/report documents. The analysis focuses on violation cases by city, service type, year, and program element category, helping identify geographic concentration, inspection patterns, and service-level distribution.

▶️ Running the Notebooks

Install the required Python dependencies:

pip install -r requirements.txt

Open Python-based project notebooks using Jupyter Notebook or VS Code:

jupyter notebook

For projects using external datasets, download the datasets from the linked sources and place them in the respective project data folders using the filenames described in each data/README.md.

🚀 Purpose

The purpose of this repository is to present practical data analytics projects in a clean, structured, and well-documented format. These projects demonstrate how real-world data can be collected, cleaned, modeled, analyzed, visualized, and reported to support interpretation, reporting, and decision-making.