About Me
I'm Bhavan, a passionate and detail-oriented Data Analyst with a knack for turning data into actionable insights. I believe in the power of data to drive smarter decisions and improve processes. My mission is to uncover valuable patterns, present them effectively, and enable data-driven strategies that bring real-world impact.
Profile Summary
- Passionate and detail-oriented Data Analyst with a strong belief in using data to drive smarter decision-making.
- Skilled in extracting, cleaning, and analyzing data to uncover meaningful insights and solve complex problems.
- Designs, builds, and maintains data pipelines and infrastructure.
- Skilled in creating interactive dashboards using Power BI and Matplotlib to monitor KPIs, trends, and performance metrics, improving decision-making efficiency.
- Uses data to evaluate product performance, user behavior, and growth opportunities.
- Strong foundation in analytical thinking, with a systematic and problem-solving mindset.
Technical Skills
Internships
Projects
Global Superstore Sales Profitability Analysis.
Analyzing the sales performance and profitability across regions and product categories in the Global Store dataset provides key insights for business strategy and growth.
- Tools Used: SQL, Python, Power BI, Pandas, Numpy
- Analyzed sales, profitability, and shipping dynamics to deliver actionable insights for improving customer satisfaction and operational efficiency.
- Built visualizations to identify high-performing products, regions, and customer segments, enabling data-informed decision-making.
Euromart Sales and Profitability Analysis
Analyzed Euromart’s historical sales data to evaluate business performance across different regions, products, and customer segments. The goal was to identify profitability trends, uncover inefficiencies, and recommend data-driven strategies to maximize revenue and operational efficiency.
- SQL, Python (Pandas, NumPy), Excel
- Used SQL to aggregate data by category, sub-category, region, and customer segment to assess revenue and order trends.
- Identified best-selling products and regions contributing most to overall revenue.
- Conducted profitability analysis using custom metrics (e.g., profit margin %, return on sales).
Pizza Sales Analysis Using SQL
Performed an in-depth analysis of pizza sales data to uncover trends in revenue, customer preferences, and operational efficiency. The objective was to support business decisions related to menu optimization, pricing, and inventory planning.
- Tools Used: MySQL, Excel, Power BI
- Imported and cleaned raw sales data using Excel, including order IDs, pizza types, order dates, quantities, and prices.
- Structured tables into normalized schemas (orders, order details, pizzas, pizza types) for efficient querying in MySQL.
- Identified top-selling pizza categories and sizes that generated the most revenue.
- Discovered sales peak during weekends and evening hours, indicating optimal staffing times.
06/2024
Blogs
Python’s Oop's Revolution
Explored how Python’s Object-Oriented Programming (OOP) features simplify code organization, enhance reusability, and support scalable application development.
Click here