I'm a B.Tech Engineering Physics student at IIT Ropar (2023–2027), recently completed my Data Analytics Intern at LinuxWorld Informatics Pvt. Ltd. I turn raw, messy data into clear business insights using SQL, Excel, Power BI and Python.

My background in physics and engineering gives me a strong analytical foundation — I'm comfortable breaking down complex problems and I bring that same rigor to data: cleaning it, querying it and visualizing it into dashboards that actually help people make decisions.

• 🔭 Currently working on end-to-end data analytics projects (SQL → Power BI/Excel dashboards)
• 🌱 Deepening my skills in DAX, Power Query and Python
• 📫 Reach me at surajk.b168@gmail.com

Languages:

Data Analysis & Visualization:

Databases:

Tools:

Power BI Excel DAX

• Built an interactive Power BI dashboard analyzing production, quality, cost, and downtime across 12 manufacturing plants in India.
• Tracked units planned vs. produced, defect rates, downtime by machine, and order fulfillment status across plants, shifts, and product lines.
• Broke down operating costs (raw material, labor, energy) by month, region, and product line to surface cost drivers.
• Key metrics: 90% overall performance, 6.22% defect rate, ₹203.99M total operating cost analyzed.

MySQL Power BI DAX

• Wrote MySQL queries (joins, aggregations, grouping) to clean and extract pizza sales data.
• Built an end-to-end Power BI dashboard tracking revenue, order trends, and product performance.
• Used DAX measures (CALCULATE, SUMX, RELATEDTABLE) with a dedicated Date table and Field Parameters for dynamic axis switching.
• Key metrics: $817.86K revenue analyzed across 21.35K orders.

Excel PivotTables Data Cleaning

• Cleaned and analyzed 220 marketing campaigns across 5 channels (Email, Google Ads, Social Media, TV, Radio) for an e-commerce company.
• Handled missing data with formula-driven imputation (ratio/rate-based estimation) instead of dropping rows, with color-coded flagging for full auditability.
• Built calculated metrics (CTR, Conversion Rate, CPC, CPA, ROI, Profit/Loss), PivotTables, and charts (stacked bar, pie, line, scatter) to compare channel performance.
• Key finding: Email delivered the best ROI (75%) on just 3% of total budget, while 29 loss-making campaigns were all concentrated in TV and Radio.

MySQL Excel Data Analysis

• Analyzed the full purchase funnel (visit → add to cart → purchase) using SQL CTEs, window functions, and self-joins on ~9,400 events from 5,000 users.
• Found email traffic converts at ~34% vs. ~7% for social traffic.
• Measured funnel drop-off timing between stages and built an Excel dashboard to visualize findings.

📁 More projects on my GitHub repositories

• B.Tech, Engineering Physics — Indian Institute of Technology, Ropar (2023–2027)
• JEE Advanced: AIR 12530 | JEE Main: 98.57 percentile | MHT-CET: 98.95 percentile

Open to Data Analyst opportunities — let's connect!

• Email: surajk.b168@gmail.com
• LinkedIn: linkedin.com/in/skb168
• GitHub: github.com/SurajB-168