# Palak Rawat (Palak Techie)

> Palak Rawat, also known as Palak Techie, is a data analyst and BS in Data Science and Applications student at IIT Madras. Palak works with SQL, Python, Pandas, Excel and Power BI to clean messy data, analyze KPIs and build dashboards that turn customer and revenue data into business decisions.

Palak Techie is the public alias of Palak Rawat; both names refer to the same person. Official website: https://palakrawat.xyz/

## Profile

- Name: Palak Rawat
- Also known as: Palak Techie
- Title: Data Analyst
- Education: BS in Data Science and Applications, Indian Institute of Technology Madras (May 2024 – Expected 2028 · CGPA 7.84 / 10)
- Website: https://palakrawat.xyz/
- Email: palak23052004@gmail.com
- LinkedIn: https://www.linkedin.com/in/palaktechie/
- GitHub: https://github.com/palak651

## Core skills and tools

- Data Analytics: Python, Pandas, NumPy, SQL, Data Cleaning, EDA, Statistical Analysis, KPI Analysis, Data Visualization
- Business Intelligence: Power BI, DAX, Dashboard Development, Data Modeling, Star Schema, Dynamic Measures
- Excel: Microsoft Excel, Pivot Tables, Lookups
- Databases: PostgreSQL, SQLite, Advanced SQL, CTEs, Window Functions, Aggregate Queries
- Machine Learning: Supervised Regression, Classification, Decision Trees, Random Forest, Feature Engineering, GridSearchCV
- Development & Tools: Git, GitHub, Jupyter, Google Colab, VS Code, Flask API, SQLAlchemy, REST, HTML5, CSS3

## Services

- Data Analysis: Cleaning, preprocessing, and exploratory analysis of real-world datasets with Python, Pandas, NumPy, and Excel to surface customer behavior, spending patterns, and KPIs.
- SQL & Databases: Business-oriented analysis in PostgreSQL and SQLite using CTEs, window functions, and aggregate queries across revenue, customer segments, channels, and churn.
- Power BI Dashboards: Interactive dashboards built on star-schema data models with DAX measures and KPIs for churn, retention, revenue, and customer lifetime value.
- Machine Learning: Supervised regression and classification with feature engineering, Random Forest, and GridSearchCV tuning, compared across multiple algorithms.
- Web & API Development: Role-based Flask and SQLAlchemy applications with REST endpoints, relational schemas, and clean HTML5 and CSS3 front ends.

## Projects

### [Customer Churn & Behavior Analysis](https://github.com/palak651/Customer-Churn-Behavior-Analysis)

- Category: Analytics
- Problem: A business with 15,000 customer records needed to know how many customers churn, which segments churn most, and where retention effort should go.
- Approach: Cleaned and validated the raw data in Python and Pandas (duplicate, invalid-age and date-consistency checks, missing values handled by business meaning), answered structured business questions in PostgreSQL, then wrote DAX measures for a 3-page interactive Power BI dashboard covering customer overview, churn and retention, and customer behavior.
- Stack: Python, Pandas, PostgreSQL, SQL, Power BI, DAX
- Results: Measured overall churn at 15.32% across 15,000 customers and about 7.31M in spending. Customers with satisfaction scores of 1-2 churned at roughly 49-50% versus under 10% for scores of 3-5, and churned customers spent less on average (347.79 vs 557.29).
- Code: https://github.com/palak651/Customer-Churn-Behavior-Analysis

### [Flight Ticket Price Prediction & Web API](https://github.com/palak651/flight-price-prediction-ml)

- Category: Machine Learning
- Problem: Predict flight ticket prices from flight-related features, a regression problem set as a Kaggle competition.
- Approach: Exploratory data analysis, missing-value and outlier analysis, categorical encoding and feature scaling, then seven regression models compared (Linear Regression, Decision Tree, Random Forest, Gradient Boosting, Extra Trees, KNN, AdaBoost) with tree-based models tuned through GridSearchCV and RandomizedSearchCV.
- Stack: Python, Pandas, NumPy, Scikit-learn
- Results: Random Forest achieved the highest validation R² of 0.9755, and predictions were generated for the Kaggle test set.
- Code: https://github.com/palak651/flight-price-prediction-ml

### [Modern Hospital Management System](https://github.com/palak651/Hospital-Management-App-V1)

- Category: Web App
- Problem: A hospital needs one system where admins, doctors and patients each see and manage only what is relevant to their role.
- Approach: Built a Flask application on SQLAlchemy and SQLite with a relational schema of 8 entities, role-based access, REST endpoints and an HTML5/CSS3 front end.
- Stack: Flask, SQLAlchemy, SQLite, HTML5/CSS3
- Results: Separate role-based dashboards for Admins (doctors, patients and appointments overview), Doctors (profile, qualification and specialization) and Patients.
- Code: https://github.com/palak651/Hospital-Management-App-V1

## Education

- Indian Institute of Technology Madras: BS in Data Science and Applications (May 2024 – Expected 2028 · CGPA 7.84 / 10)
- Lady Irwin College, University of Delhi: B.Sc. in Home Science (2021 – 2024 · CGPA 8.64 / 10)
- D.S. Science Academy, Gangapur City: Rajasthan Board (RBSE) (2019 – 2021 · Class XII 95.0% · Class X 88.8%)

## Certifications

- Data Mining, NPTEL, IIT Kharagpur
- Human Behaviour, NPTEL, IIT Guwahati

## Achievements

- Winner, Ship Happens 2026, a student hackathon organised by AWS Student Builder Group ADGIPS, Delhi NCR (31 October 2026)
- All India Rank 196 (out of 15,000+ teams), National Entrepreneurship Challenge (NEC), IIT Bombay

## FAQ

### Who is Palak Rawat?

Palak Rawat is a data analyst and BS in Data Science and Applications student at IIT Madras (expected 2028). Palak works with SQL, Python, Pandas, Excel and Power BI on data cleaning, KPI analysis and dashboards that turn customer and revenue data into decisions.

### Who is Palak Techie?

Palak Techie is the online name of Palak Rawat, the data analyst and IIT Madras Data Science student behind palakrawat.xyz. Palak Techie and Palak Rawat are the same person.

### What does Palak Rawat specialize in?

Data analysis and business intelligence: cleaning and exploring real-world datasets in Python and Pandas, business analysis in SQL (PostgreSQL, CTEs, window functions) and interactive Power BI dashboards built on star-schema models with DAX. Palak also builds machine learning models with scikit-learn and web apps with Flask.

### What projects has Palak Rawat built?

A customer churn and behavior analysis of 15,000 customers (15.32% churn, 3-page Power BI dashboard), a flight ticket price prediction model comparing 7 regression models (best validation R² of 0.9755) and a role-based hospital management system in Flask and SQLAlchemy.

### What has Palak Rawat achieved?

Palak won Ship Happens 2026, a student hackathon organised by AWS Student Builder Group ADGIPS in Delhi NCR, and ranked All India 196 out of 15,000+ teams in the National Entrepreneurship Challenge at IIT Bombay.

### How can I contact Palak Rawat?

Email palak23052004@gmail.com, or connect on LinkedIn and on GitHub as palak651.

## Links

- [Portfolio](https://palakrawat.xyz/): projects, skills, education and contact
- [LinkedIn](https://www.linkedin.com/in/palaktechie/)
- [GitHub](https://github.com/palak651): source code for all projects