Data Analyst — turning raw data into decisions.
Skilled in Python, Power BI, SQL & Advanced Excel.
Analyzed e-commerce data to identify revenue and customer trends.
Used Python for data cleaning, EDA and visualization.
Improved sales strategy efficiency by 15%.
Generate QR codes from text, URLs, or UPI IDs.
User-friendly Tkinter interface.
Save QR codes as .png images.
Quick and lightweight.
Chat with Gemini AI in real-time.
Uses the Gemini-1.5-Flash model for generating responses.
Simple CLI interface.
Supports continuous conversation until the user exits.
Used SQL for real-world business problem solving.
Generated insights for decision-making, not just queries
Identified employee behavior patterns through SQL-based trend analysis.
Performed comprehensive data exploration and validation on real-world datasets
Used advanced SQL concepts like: JOINs,(INNER, LEFT, RIGHT),GROUP BY & HAVING ,CASE Statements ,Subqueries & CTEs ,Window Functions (RANK, ROW_NUMBER, AVG OVER)
Transaction fraud detection
Loan repayment tracking
Customer segmentation (active, dormant, multi-account, city-wise, etc.)
Monthly and city-wise spending analyses
Top performing customers and loan officers
Average balances and lifetime value reporting
Identify currently admitted patients, room/bed occupancy, frequent diagnoses
Calculate hospital and departmental revenue; analyze average bill per department/gender
Track admissions per department/month/day; monitor insurance provider trends
List patients with unpaid/pending bills, and summarize payment status totals
List patients with unpaid/pending bills, and summarize payment status totals
Analyze stay duration per department and room utilization rates
Top watched movies/TV shows and trending titles by region
Genre and device usage analytics
User-level metrics: average watch time, completion rate, activity, ratings
Engagement comparison across subscription types
Region-wise and daily viewing trends
Inactive user detection for retention campaigns
Automated data refresh and report generation workflows.
Saved approximately 5 hours per week in operational reporting.
Built interactive dashboards with drill-down capabilities.
Created HR KPI dashboard tracking headcount, attrition & salary bands.
Used DAX time intelligence for YoY comparison metrics.
Enabled HR team to reduce reporting time by 3 hours/week.
Built a dynamic budget vs actual tracker using Pivot Tables.
Used conditional formatting to highlight variances automatically.
Created monthly summary charts for quick executive review.
Interactive Excel dashboard with slicers and dynamic charts.
Used VLOOKUP, INDEX-MATCH for multi-sheet data consolidation.
Automated monthly reports using Excel Macros (VBA).
• Collected, cleaned, and analyzed large datasets using Excel, SQL, and Python (Pandas, NumPy) to extract actionable insights.
• Designed and maintained Power BI dashboards, improving business data visibility and reporting efficiency by 40%.
• Performed data validation and integrity checks across multiple sources, ensuring 98% reporting accuracy.
I'm open to Data Analyst roles, freelance projects, and collaborations. Whether you have a project idea or just want to talk data — feel free to reach out!