Hi, I'm Raj Kumar Sunar — a data analyst specialising in Python, SQL, and Power BI. I work across retail, finance, and tech to answer the question businesses keep avoiding: not "what happened?" but "what should we do next?"
Early in my career, I thought visual complexity meant success. I focused on fancy slicers and complex charts. But in the vast field of data, stakeholders didn't need complexity. They needed answers.
The new roadmap: Target the Problem → Ask the Hard Questions → Synthesize pieces of information → Prescribe the Solution.
I believe in using the right tool for the job. Whether it's Python for heavy lifting, SQL for extraction, or Tableau for storytelling.
Pandas, NumPy, Scikit-Learn
PostgreSQL, MySQL, Window Functions
DAX, Power Query, Modeling
LOD Expressions, Storyboarding
Hypothesis Testing, A/B Testing
Version Control, Deployment
Real-world projects solving real business problems. From ETL pipelines to predictive dashboards.
📊 Super Store Sales Analysis (Excel Dashboard)Analyzed Super Store sales data to uncover key insights on product performance, regional trends, and profitability. The dataset contained raw transactional data that required cleaning, structuring, and transformation to make it suitable for analysis.Performed data cleaning and transformation using Power Query, including removing duplicates, correcting data types, and creating conditional and custom columns. Built a data model and calculated KPIs using Power Pivot, and conducted time-series analysis by extracting year, month, and weekday/weekend from the date field. Developed multiple Pivot Tables to analyze sales trends, category performance, and regional distribution.Designed an interactive Excel dashboard (Dashboard-1) using charts, KPI cards, and slicers to enable dynamic exploration of the data.Key insights include identifying the Cannon ImageClass 220 Advanced Copier as the top-selling product, Technology as the highest revenue-generating category ($21.49K), and the West region contributing the most sales (31%). The analysis also revealed that Phones are the most in-demand sub-category and that sales follow a consistent upward trend, peaking in December 2017.
Excel Pivot Tables DashboardCoffee shop sales analysisThe business questionA coffee shop owner needed to understand which products, times of day, and customer patterns were actually driving revenue — and where operational inefficiency was quietly costing money.What I didCleaned and structured 12 months of transactional data in Excel. Built dynamic Pivot Table dashboards segmented by product category, hour of day, and day of week. Applied VLOOKUP and IF-based formulas to flag underperforming SKUs and surface revenue concentration risk.Key findingMorning hours (7–10am) generated 61% of daily revenue despite representing only 23% of operating hours — recommending targeted staffing and upsell strategies during that window could lift daily revenue by an estimated 8–12%.
Emirated customer reviews data analysis
Thoughts on Data, Python, and the Industry.
Explainable AI (XAI): Opening the Black Box of Machine Learning
You're Learning the Wrong Thing About Data Visualization
AI is not magic. It's a very powerful tool that still needs a smart human directing it. Use it to eliminate the repetitive, the predictable, and the soul-crushing — and spend your freed-up time doing the creative, strategic work that only you can do.The marketers winning right now aren't the ones ignoring AI, and they're not the ones blindly trusting it either. They're the ones who've figured out the collaboration. That's the game.
Job hunting can feel like an Olympic sport — except no one gives you a medal, and the hurdles keep getting higher. But here’s one mistake almost everyone makes:
Microsoft/Coursera • 2026
IBM • 2025
DataCamp • 2025
Hi! Ask me about Raj's skills or projects.
