I'm Naman Kumar, a data analyst with hands-on experience in Power BI, SQL, Python (Pandas), and Excel. I specialize in data cleaning, visualization, and dashboard reporting to drive business insights. I enjoy turning messy data into clear, actionable stories that help teams make smarter decisions. My work focuses on practical impact, data quality, and delivering measurable improvements in areas like inventory optimization, churn analysis, and revenue reporting.…

Naman Kumar

I'm Naman Kumar, a data analyst with hands-on experience in Power BI, SQL, Python (Pandas), and Excel. I specialize in data cleaning, visualization, and dashboard reporting to drive business insights. I enjoy turning messy data into clear, actionable stories that help teams make smarter decisions. My work focuses on practical impact, data quality, and delivering measurable improvements in areas like inventory optimization, churn analysis, and revenue reporting.…

Available to hire

I’m Naman Kumar, a data analyst with hands-on experience in Power BI, SQL, Python (Pandas), and Excel. I specialize in data cleaning, visualization, and dashboard reporting to drive business insights. I enjoy turning messy data into clear, actionable stories that help teams make smarter decisions.

My work focuses on practical impact, data quality, and delivering measurable improvements in areas like inventory optimization, churn analysis, and revenue reporting.

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Language

English
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Hindi
Advanced

Work Experience

Add your work experience history here.

Education

B.Tech in CSE(AI) at KIET Group of Institutions
January 1, 2023 - January 1, 2027
CBSE Class 12th at DPSG Meerut Road
January 1, 2022 - January 1, 2022
CBSE Class 10th at DPSG Meerut Road
January 1, 2021 - January 1, 2021

Qualifications

Data Modeling in Power BI
January 11, 2030 - March 23, 2026
Extract, Transform and Load Data in Power BI
January 11, 2030 - March 23, 2026
SQL (Intermediate)
January 11, 2030 - March 23, 2026
SQL (Intermediate) – Hackerrank
January 11, 2030 - March 23, 2026

Industry Experience

Retail, Software & Internet, Professional Services, Education
    paper Retail Inventory & Sales Analysis — Python — PostgreSQL — Power BI

    • Analyzed a retail dataset containing 12+ million records across multiple tables including inventory, purchases, sales, purchase
    prices, and vendor invoices.
    • Utilized SQL in PostgreSQL to perform joins and aggregations across six tables and generated a consolidated 10,000-row summary
    dataset for analysis.
    • Conducted data cleaning, exploratory data analysis, and feature engineering in Python using Pandas, creating metrics such as
    gross profit, profit margin, stock turnover, sales-to-purchase ratio, and unsold capital.
    • Built an interactive Power BI dashboard visualizing top brands by sales, vendor performance, low-performing vendors, and KPI
    indicators including total sales, total purchases, gross profit, profit margin, and unsold capital.

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