Data analytics project showcasing Medical data Analysis using SQL . Here’s a professional, polished README you can use for your Medical Queries SQL data analysis project on GitHub. It’s structured to clearly explain what you did, why it matters, how someone else can run it, and what insights you found — just replace the placeholder parts (in brackets) with your actual project details.
Medical Data Analysis using SQL
Data analytics project showcasing medical data exploration and insights using SQL.
🩺 Project Overview
This repository contains an end-to-end medical data analysis project using SQL queries. The goal of this project is to extract meaningful insights from healthcare-related datasets, answer key analytical questions, and demonstrate proficiency in SQL for data exploration, aggregation, and reporting.
SQL is used to query multiple related tables (e.g., patients, doctors, admissions) to derive business-relevant insights that can help healthcare stakeholders understand trends in patient demographics, hospital admissions, diagnoses, doctor workloads, and regional health patterns.
📂 Project Contents File Description medical_quaries.sql Main SQL script with queries used for analysis patients.csv Patient demographic data doctors.csv Doctor information admissions.csv Hospital admissions and case details province_names.csv Province / region lookup table Medical_Data_History.pdf Supporting documentation (if any) README.md This file 🧠 Objectives
This project focuses on:
Exploring the structure of medical and healthcare data
Writing SQL queries to answer analytical questions
Using data aggregation, filtering, joins, and group operations
Generating summaries and insights relevant to healthcare services
📊 Key Questions Answered
The SQL queries are designed to answer business-relevant questions such as:
Patient Demographics
What is the distribution of patients by age, gender, or province?
Which age group has the highest admission rate?
Doctor & Hospital Analysis
Which doctors have the most patient interactions?
What are the admission counts for each doctor?
Admission Insights
How many total admissions occurred in the dataset?
What are the most common diagnoses among admitted patients?
Regional Patterns
Which provinces have the highest patient inflow?
Are there regional trends in hospital visits?
(Tip: Add your actual insights here with top takeaways — 3–5 bullets summarizing the most interesting results.)
🛠️ Tools & Technologies
This project uses:
SQL for data querying and analysis
Any SQL database engine (e.g., MySQL, PostgreSQL, SQLite)
CSV datasets loaded into your database of choice
📥 How to Run This Project
To run this analysis on your machine:
Clone the repository:
git clone https://github.com/adithyarallabandi-alt/Medical_quaries-project-SQL.git
Load the datasets into your SQL database:
Use your SQL engine’s import tool to load .csv files into tables matching the file names.
Ensure table schema matches CSV columns exactly (or adjust as needed).
Execute SQL Queries:
Open medical_quaries.sql in your SQL client.
Run the queries one by one to reproduce the analysis.
Review Results:
Examine the query outputs to understand patterns in the data.
✨ Tips for Enhancement
Here are some ideas if you continue improving this project:
✔ Add explanatory comments above each SQL query for clarity.
✔ Include sample output screenshots or .txt result snippets in your README.
✔ Visualize results using a BI tool like Power BI or Tableau to make findings more accessible. Reddit
✔ Add sections for limitations, assumptions, and next steps for future work. I am R. Adithya, a 2nd-year BBA student aspiring to become a Data Analyst / Business Analyst. This SQL project highlights my analytical thinking and practical SQL skills and is part of my preparation for securing a data analytics internship.
🧾 License
This project is licensed under the MIT License — feel free to use and build upon this work with proper attribution.