Vishweshwar

About

Business Analyst / Data Analyst with hands-on experience in SQL, Python, Power BI, data profiling, process analysis, and KPI-driven business insights. Experienced in analyzing large datasets, identifying data quality and operational gaps, and translating findings into actionable recommendations.

Experience

• Data Science Intern
  CodeSoft
  May 2025 – Jun 2025

Education

• Bachelor of Business Administration (BBA)
  Woxsen University
  Data Science and Artificial Intelligence · 2026

Skills

• SQL <3 months
• Python <3 months
• Data Cleaning <3 months
• Feature Engineering <3 months
• Matplotlib <3 months
• NumPy <3 months
• Pandas <3 months
• Streamlit <3 months
• scikit-learn <3 months
• DAX <3 months
• Seaborn <3 months
• LLM evaluation <3 months
• Root Cause Analysis <3 months
• Data validation <3 months
• Statistical Analysis <3 months
• KPI Analysis <3 months
• Data profiling <3 months

Tools / apps / platforms

• GitHub <3 months
• Jupyter Notebook <3 months
• Microsoft Excel <3 months
• Microsoft Power BI <3 months
• n8n <3 months
• Power Query <3 months
• Tableau <3 months

Projects

• Rapido Business Case Study
  Business Analysis, Market Research, Python, Manim

  Conducted a detailed analysis of Rapido’s business journey, examining its growth timeline, business model, goals, challenges, operational context, and key business risks. Applied business analysis, market research, and strategic thinking to understand Rapido’s growth journey, competitive landscape, market positioning, and the factors influencing its business operations. Developed a complete animated business case study using Python and Manim, transforming research into visual storytelling through timelines, business concepts, analytical insights, and structured communication.

• OLA Ride Booking Data Analysis
  SQL, Power BI

  Analyzed 100,000+ ride booking records, finding a 62.09% successful booking rate and 28.1% cancellation rate to evaluate operational performance. Executed 15+ SQL queries across booking, vehicle, and customer datasets to validate metrics, analyze cancellation reasons, and identify operational patterns. Built an interactive Power BI dashboard tracking bookings, cancellations, revenue, ratings, and vehicle performance; identified actionable business recommendations.

• Customer Shopping Trends Analysis
  Python, SQL, Power BI

  Analyzed 3,900 customer purchase records, with 68.0% male customers and Clothing representing 44.5% of purchases, to identify customer and product trends. Used Python and SQL to analyze category performance, seasonal demand, customer segments, and purchase behavior; average purchase value was $59.76.

Courses & certifications

• Google Data Analytics Professional Certificate · Coursera · 2025
• Case Crunch Competition · Century R · 2024
• NCC 'A' Certificate Holder · National Cadet Corps