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Coding89/README.md

Hi there 👋

🌟 Financial Data Administrator | Tech for Good

I manage complex financial pipelines for a transnational refugee organisation with primary focus on Thailand whilst building modern analytics solutions and side projects related to financial and organisational datasets. I transform messy payment data into clear and actionable visual insights.


Technical toolkit

  • ☁️ Cloud Platforms: google cloud platform
  • 🗄️Databases & querying: SQL, DuckDB
  • 📊📈 Data Visualisations: Power BI, Excel 𓊂,
  • 🖳 Libraries & Frameworks: python (pandas, pyarrow, plotly, Matplotlib, Jupyter Notebook, numpy)
  • 💱 Fintech Platforms: stripe, PayPal, Salesforce

Current Projects:

  • Currently mastering: DuckDB 🦆
  • 🤖 Current side project/s: currently working on a Python and SQL project related to charity donations/finance.

Fun facts:

💡 DuckDB Fun Fact:

🦆 DuckDB was named after ducks due to the creator, Hannes Muhleisen's fascination of watching ducks. He found them to be highly resilient, efficient and could live off anything. Ducks are adapable on air, land and water. He envisioned DuckDB operating in a seamless process across different data environments without the need for a heavy server setup.

github contribution grid snake animation

Popular repositories Loading

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    Consolidates Stripe .csv files (including all formats and accessing different YYYY folders) into one readable file. The data is readable/accessed in a parquet file.

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    This project tracks ai-investments focusing on 3 companies (Meta, Google and OpenAI) to chart the growing importance of AI. The data is visualised using PowerBI and Pandas/Matplotlib/Seaborn

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    A robust data integration pipeline that cleans, standardises and consolidates 9 years of historical National Churches Trust (360Giving) grant datasets in an optimised schema Parquet dataset.

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