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pttd1997/README.md

Hi There 👋

I’m a curious Master's student specializing in Advanced Analytics and Big Data. I believe that behind every number is a story waiting to be told. I use my skills in advanced analytics to transform complex datasets into actionable insights, helping to drive smarter, data-driven decisions.

Here you’ll find my passion projects, from building predictive models to creating insightful dashboards. Let's connect and build something cool!

🌐Socials

LinkedIn Portfolio

💻Tech Stack

Python SQL R MySQL NumPy Pandas C++ Oracle AWS PyTorch scikit-learn

Tableau Excel NotebookLM Looker Studio Shiny

Popular repositories Loading

  1. coffee-analytics-streamlit-app coffee-analytics-streamlit-app Public

    An interactive Streamlit dashboard built for a Python coursework project, offering business insights for F&B, especially coffee shops. It features ABC and FRM analyses for store and chain-level per…

    Python

  2. callcenter-dashboard-excel callcenter-dashboard-excel Public

    Based on my hands-on experience working in a call center, I came up with the idea to create a dashboard for monthly reporting. This project involved several key steps, including data preprocessing,…

  3. market-basket-analysis-fpgrowth market-basket-analysis-fpgrowth Public

    Market basket analysis using the FP-Growth algorithm on a transactional dataset, implemented in PySpark on Databricks.

    Jupyter Notebook

  4. happy-countries-2024 happy-countries-2024 Public

    Analyzing global happiness trends using the 2024 World Happiness Report (R)

    R

  5. coffee-shop-dashboard-tableau coffee-shop-dashboard-tableau Public

    An interactive Tableau dashboard visualizing coffee shop sales and customer behavior. Built to highlight trends, peak hours, and spending patterns—reimagining a dataset previously used in my Python…

  6. exploratory-data-analysis-and-K-means--cluster exploratory-data-analysis-and-K-means--cluster Public

    🔍 This project demonstrates EDA—a core skill for Data Analytics, Data Science, and Data Engineering—combined with feature engineering and K-Means clustering to segment retail banking customers.

    Jupyter Notebook