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SreejaBethu/README.md

๐Ÿ‘‹ Hi there! I'm Sreeja Bethu

๐ŸŽฏ Data Analyst | Aspiring Business Analyst | Insight-Driven Storyteller

I'm passionate about transforming data into actionable insights that drive strategic decisions and measurable outcomes. With a strong foundation in both data analytics and business understanding, I specialize in uncovering trends, solving real-world problems, and helping organizations make data-backed decisions.

I enjoy working with large datasets, building dashboards, and generating reports that speak the language of business. From cleaning raw data to visualizing key metrics, I make sure every data point counts.

๐Ÿงฐ Skills & Tools

๐Ÿ‘ฉโ€๐Ÿ’ป Programming & Query Languages

Python โ€“ Data manipulation (Pandas, NumPy), analysis, and automation

SQL โ€“ Advanced querying, joins, CTEs, window functions, and optimization

Excel โ€“ Functions, pivot tables, dashboards, and VBA basics

๐Ÿ“Š Data Visualization

Power BI โ€“ Interactive dashboards and data storytelling

Tableau โ€“ Dynamic reports and visual analytics

Matplotlib / Seaborn / Plotly โ€“ Python-based visualizations

๐Ÿ› ๏ธ Data Handling & Workflow

ETL Processes โ€“ Cleaning, transforming, and loading structured data

PIs & Web Scraping โ€“ Requests, BeautifulSoup

Git & GitHub โ€“ Version control and collaborative development

Jupyter Notebook / Google Colab โ€“ Exploratory data analysis notebooks

๐Ÿ’ผ Featured Projects

Here are a few projects that reflect my skills and problem-solving capabilities:

Leverages LLMs and AI agents to automatically analyze reports (PDF/Excel/CSV) and generate actionable summaries, charts, and insights.

๐Ÿ” Automated insight extraction using Python & OpenAI APIs

๐Ÿ“Š Visualizations using Plotly and Matplotlib

๐Ÿค– Intelligent summarization & natural language generation


An interactive Streamlit application visualizing and comparing cost of living indices across various countries.

Technologies Used: Python, Streamlit, Pandas, Plotly, Seabornโ€‹

Features:

  • ๐Ÿ—บ๏ธ Compare indices by country using visual charts

  • ๐Ÿ“Š Built with Plotly, Seaborn, Streamlit

  • ๐Ÿงฎ Focus on rent, groceries, utilities, etc.

    Outcome: Facilitates users in making informed decisions regarding global cost comparisons.


Analyzes sales data and builds time-series models to forecast future trends.

  • ๐Ÿงผ Data wrangling and preprocessing with Pandas
  • ๐Ÿ“ˆ Time-series forecasting with ARIMA & statsmodels
  • ๐Ÿ“‰ Actionable sales insights for business planning

๐Ÿ“ฌ Letโ€™s Connect

Iโ€™m always excited to collaborate, learn, or just chat about data!

๐Ÿ”— LinkedIn

๐Ÿ“ง Email: [email protected]

๐Ÿง  Portfolio Website: https://sreejabethu.github.io/

๐Ÿ“ Location: United States (Open to Remote & Hybrid Roles)

Pinned Loading

  1. Smart-Report-Analyzer Smart-Report-Analyzer Public

    An AI-powered LLM app to analyze and summarize Excel, CSV, and PDF reports using Hugging Face language models. Built with Streamlit.

    Python 1

  2. Cost-Of-Living-Index-Globally Cost-Of-Living-Index-Globally Public

    This Streamlit app is a data visualization tool that allows users to explore and compare the cost of living indices across different countries. The app takes in a dataset of cost of living indices โ€ฆ

    Python 1

  3. Forecasting-Weather Forecasting-Weather Public

    Weather Forecasting using OpenWeatherMap API and Random Forest Regressor in Python. Converts temperature data to Fahrenheit, and provides visualizations for actual vs predicted temperatures.

    Python 1

  4. Paris-Olympics-2024-Medals-List Paris-Olympics-2024-Medals-List Public

    Python 1

  5. Realtime-Stock-Market-Analysis-Visualization Realtime-Stock-Market-Analysis-Visualization Public

    Python 1

  6. agent-starter-pack agent-starter-pack Public

    Forked from GoogleCloudPlatform/agent-starter-pack

    A collection of production-ready Generative AI Agent templates built for Google Cloud. It accelerates development by providing a holistic, production-ready solution, addressing common challenges (Dโ€ฆ

    Python