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mjshubham21/readme.md



πŸ‘‹ Hey, I'm Shubham β€” nice to meet you!

✨ Transitioning from web development into data analytics, I fuse a builder's instinct with an analyst's curiosity to turn raw numbers into decisions people actually act on.

I live at the intersection of:

πŸ“Š  Data & Business Intelligence
πŸ’»  Software Engineering
πŸ€–  Generative AI
🎨  Creative Web Experiences

I bring a strong commercial lens to everything I build β€” dashboards aren't just charts, and code isn't just syntax. Both need to move the needle. πŸ“ˆ


flowchart TD
    A["πŸ“Š RAW DATA"] --> B["πŸ’‘ INSIGHT"]
    B --> C["πŸ’Ό BUSINESS VALUE"]
    B --> D["πŸš€ PRODUCT VALUE"]
    C --> E["🌟 IMPACT"]
    D --> E

    style A fill:#0D1117,stroke:#00F0FF,stroke-width:2px,color:#00F0FF
    style B fill:#0D1117,stroke:#7B2CBF,stroke-width:2px,color:#7B2CBF
    style C fill:#0D1117,stroke:#0066FF,stroke-width:2px,color:#0066FF
    style D fill:#0D1117,stroke:#FF0080,stroke-width:2px,color:#FF0080
    style E fill:#0D1117,stroke:#FFD700,stroke-width:2px,color:#FFD700
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🎯 Core Focus: Extracting intelligence 🧠, engineering seamless applications 🌐, and weaving Generative AI πŸ€– into everyday workflows.


πŸ“Š Data Analytics & AI




πŸ’» Full Stack Development


Data, ideas, and caffeine β˜• β€” turned into things that (hopefully) matter.

🎬 MoviesMetrics

End-to-end movie industry analytics pipeline

MoviesMetrics Dashboard
🎯 Focus Box office & studio-level insights
🧩 Pipeline Data ingestion β†’ cleaning β†’ BI layer
πŸ› οΈ Stack Python Β· Power BI

πŸ“€ DVD Rental Analytics

SQL-powered business intelligence

SQL Maven Movies
🎯 Focus Revenue & customer behavior
🧩 Pipeline Raw tables β†’ BI-grade SQL queries
πŸ› οΈ Stack SQL Β· PostgreSQL

🏑 AirBnB Insights

Exploratory analysis of listings data

AirBnB Python Analysis
🎯 Focus Pricing patterns & location trends
🧩 Pipeline Cleaning β†’ EDA β†’ visual storytelling
πŸ› οΈ Stack Python Β· Pandas Β· Seaborn

πŸ›’ Retail Sales Analytics

Interactive retail KPI dashboard

Retail Sales Dashboard
🎯 Focus KPI monitoring & sales performance
🧩 Pipeline Excel prep β†’ Tableau storytelling
πŸ› οΈ Stack Tableau Β· Excel

AreaWhat I'm doing
πŸ“ŠΒ Β Data AnalyticsTurning messy data β†’ meaningful insights
πŸ€–Β Β Generative AIExploring AI-powered workflows & products
🌐  Full StackBuilding useful things for the web
πŸ§ͺΒ Β ExperimentingAlways breaking things to understand them
🎲 Click for a random dev-fact about me

πŸŒ™ I do my best debugging after midnight. β˜• Coffee-to-commit ratio: roughly 1:1. πŸ“ˆ I've stared at more dashboards than Netflix recommendations. 🧩 Half my browser tabs are Stack Overflow. The other half is documentation I'll "read later."

Meet my contribution snake β€” it lives off my commit graph and only grows if I keep showing up. 🐍

github contribution snake animation

βš™οΈ Powered by a GitHub Action that re-renders the snake daily from your real contribution graph β€” setup file below.


GitHub Stats Top Languages






🧠 Think deeply. Β Β Β  πŸ“Š Measure everything. Β Β Β  πŸš€ Build boldly.

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  1. Python_DA Python_DA Public

    My Python learning journy repository for Data Analytics. JSON School.

    Jupyter Notebook 1

  2. Excel_Adidas_US_Sales Excel_Adidas_US_Sales Public

    Data analysis of Adidas Sales in US from year 2020-21 using MS Excel.

  3. SQL_maven_movies_project SQL_maven_movies_project Public

    A project in SQL, dataset is from Maven Analytics about Movie DVD rental bussiness.

  4. AirBnB_Python_Project AirBnB_Python_Project Public

    Data analysis of AirBnB data using Python and its Data Analysis Libraries.

    Jupyter Notebook

  5. MoviesMetrics_PowerBi_Python_Project MoviesMetrics_PowerBi_Python_Project Public

    Comprehensive Power BI dashboard analyzing global movie revenue, ratings, and ROI, complemented by Python-driven data cleaning and advanced DAX measures for dynamic insights.

    Jupyter Notebook

  6. BritishAirways_Tableau_Project BritishAirways_Tableau_Project Public

    Interactive Tableau dashboard analyzing British Airways customer reviews to uncover insights on passenger satisfaction, service quality, and route performance.