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Subham-Adhikari/README.md

Hi, I'm Subham Adhikari

Data Analyst | SQL • Power BI • Excel

LinkedIn Email Resume

Data Analyst who loves finding stories in data. I work with SQL, Power BI, and Excel to clean messy datasets and build dashboards that actually help make decisions. My portfolio includes projects analyzing $2.33M+ in sales data and 60K+ transactions. Currently leveling up my skills with Python. Feel free to explore my work and connect!

Dedicated to solving real-world business challenges through structured thinking and modern data technologies.

🛠️ Technical Stack


Leveraging a robust technical stack to transform raw data into actionable business intelligence.

⚡ Fun Fact

"Instead of finding a relationship with someone special, I’m now finding relationships between tables. I believe that data is only as good as the decisions it enables."

Popular repositories Loading

  1. Subham-Adhikari Subham-Adhikari Public

  2. sales-performance-eda sales-performance-eda Public

    Exploratory Data Analysis of 60K+ sales transactions using SQL (MSSQL) to uncover customer segments, product performance, and operational insights.

    TSQL

  3. road-accident-analysis-dashboard road-accident-analysis-dashboard Public

    UK Road Accident Analysis built entirely in Excel using Power Query for data cleaning and modeling, with interactive charts to explore accident trends and severity patterns.

  4. steel-sales-performance-dashboard steel-sales-performance-dashboard Public

    Steel Sales Performance Dashboard built using Power BI, analyzing regional sales, revenue trends, and product-level insights with an optimized data model.

  5. electronics-sales-analysis-dashboard electronics-sales-analysis-dashboard Public

    Interactive Power BI electronics sales analysis dashboard to identify key products, revenue drivers, and monthly performance patterns.

  6. products-sales-and-profitability-dashboard- products-sales-and-profitability-dashboard- Public

    Power BI dashboard analyzing $2.33M in superstore sales (2020-2023) using custom DAX and time intelligence to uncover profitability patterns, customer segments, and product performance insights.