Rachana N

About Me

I am a passionate Data Analyst and Data Science enthusiast with a strong interest in turning data into actionable insights. I specialize in data cleaning, visualization, and predictive modeling, helping to uncover trends and support informed decision-making. My skills include Python, Pandas, SQL, Flask, PHP, MySQL, and API integrations, giving me the ability to handle both analytics and development tasks. I enjoy building projects that combine data-driven insights with full-stack applications, making them practical and impactful. With a focus on accuracy, problem-solving, and scalability, I aim to deliver solutions that address real-world business challenges..

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Profile Summary

  • Data Analyst: Skilled in data analysis, automation, and visualization, with the ability to apply analytical techniques to extract insights, structure data, and support effective decision-making..

  • Technical Expertise: Proficient in Python, SQL with strong knowledge of data cleaning, preprocessing, and database management (MySQL). Skilled in using libraries such as Pandas, NumPy, Scikit-Learn, Matplotlib, and Seaborn.

  • Automation Skills: Capable of developing Python-based automation workflows to streamline reporting and notifications, reducing manual tasks.

  • Visualization Proficiency: Skilled in creating dashboards and data visualizations using Matplotlib, and Seaborn for monitoring KPIs and business trends.

  • Machine Learning Foundations: Hands-on knowledge of supervised and unsupervised learning techniques using Scikit-Learn, applying predictive analytics to extract insights from datasets..

  • Possess strong database management skills, with knowledge of optimizing data storage and retrieval using MySQL.

Technical Skills

Python
SQL
Pandas
Seaborn
Data Processing
Data Cleaning
EDA
MySQL
Data Visualization
Machine Learning
Scikit-Learn
Git
GitHub
Statistics
Web Scraping

Dashboard | Reporting | KPI
Soft Skills
Problem-Solving, Analytical Thinking, Collaboration

Internships

DataScience and Machine Learning

Analogica Software Dev Pvt Ltd

06/2025 – Present

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  • Gained hands-on experience in data preprocessing, feature engineering, and exploratory data analysis (EDA) on real-world datasets.
  • Built and evaluated predictive models using classification algorithms, applying optimization and hyperparameter tuning techniques.
  • Designed data visualizations with Matplotlib and Seaborn to interpret trends and communicate insights effectively.
  • Strengthened database management skills by working with MySQL for querying, data extraction, and storage optimization.
  • Collaborated in end-to-end ML workflows, including version control with Git and deployment of models using Render.

Certificates

  • Data Science with Python .
  • Data Science Methodology
  • Python Project for Data Science
  • Fundamentals of Al and ML

Projects

SmartSales Elite Reporter

SmartSales Elite Reporter – An automated sales reporting system that collects data, generates PDF reports, emails stakeholders, and provides real-time dashboards for admins.

  • Tools Used: Python, Flask, Google Forms/Custom HTML, Google Sheets/SQLite, SMTP/Gmail, PDF Generation (ReportLab/Gemini API).
  • Automated the collection, storage, and reporting of sales data, eliminating manual effort.
  • Integrated Google Forms/HTML forms with Google Sheets and SQLite for structured data management.
  • Designed workflows to capture form submissions, generate PDF reports, and trigger automated emails.
  • Implemented automated report emails to stakeholders, ensuring instant updates and transparency.
  • Configured admin notifications to provide real-time alerts of new sales entries.
  • Generated dashboards with visual summaries for quick insights into sales performance.
  • Workflow covered: Form Submission → Google Sheets/SQLite → Report Generation → Email Notification → Dashboard .

GitHub Repo: SmartSales Elite Reporter

Breast Cancer Prediction

Breast Cancer Prediction – An AI/ML-based system that analyzes patient data, predicts the likelihood of breast cancer, and provides actionable insights for early detection and decision-making.

  • Tools Used: Python, Scikit-learn, Pandas, NumPy, Matplotlib/Seaborn, Jupyter Notebook, Pickle (for model saving), Flask (for web interface).
  • Collected and preprocessed patient data for analysis and modeling.
  • Built machine learning models to predict breast cancer with high accuracy.
  • Implemented data scaling and feature engineering for better model performance.
  • Saved trained models using Pickle for deployment and real-time predictions.
  • Developed a Flask-based web interface to allow users to input data and get predictions.
  • Visualized data and model results using Matplotlib and Seaborn for better insights.

GitHub Repo: Breast Cancer Prediction

Happiness Prediction

Happiness Prediction – A machine learning system that analyzes socioeconomic and survey data to predict happiness scores and provide actionable insights for well-being improvement.

  • Tools Used: Python, Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn, Jupyter Notebook, Pickle (for model saving), Flask (for web interface).
  • Collected and preprocessed survey and socioeconomic data for analysis.
  • Built regression and classification models to predict happiness scores.
  • Implemented feature engineering and scaling to improve model accuracy.
  • Saved trained models using Pickle for deployment and real-time predictions.
  • Developed a Flask-based web interface for users to input data and get happiness predictions.
  • Visualized data trends and model performance using Matplotlib and Seaborn.

GitHub Repo: Happiness-Prediction

Sage Transportation Management System

Sage Transportation Management System – A full-stack platform that automates vehicle rentals, manages bookings, and provides real-time tracking and reporting for fleet operations.

  • Tools Used: HTML, CSS, JavaScript, PHP, MySQL, Bootstrap, Visual Studio Code.
  • Developed a full-stack vehicle rental platform for managing bookings and fleet operations.
  • Implemented user authentication and role-based access for customers and admins.
  • Integrated database (MySQL) to store vehicle, booking, and user data efficiently.
  • Designed responsive frontend interfaces using HTML, CSS, JavaScript, and Bootstrap.
  • Enabled real-time booking management, vehicle availability tracking, and reporting.
  • Ensured smooth user experience with interactive forms, search, and filtering features.

GitHub Repo: Sage Transportation Management System

Blogs

The Fusion Scroll – Merging, Joining & Stacking Data

Explored how the Fusion Scroll combines scattered datasets by merging, joining, and stacking, making them easier to use. Showed how it creates strong data connections for better insights and analysis.

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The Query Trials – Filtering Truth in a Sea of Data

Highlighted how the Query Trials use filters and conditions to find the right information in large datasets. Showed how it works like a detective solving data mysteries with precision.

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Linear Regression

Presented how Linear Regression helps identify relationships between variables by fitting a straight line. Demonstrated how it predicts outcomes, making it useful for trends, forecasting, and decision-making.

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