A Data Analyst passionate about turning data into actionable insights.
I specialize in leveraging analytical tools and techniques to solve complex problems and support informed decision-making.
- 🔍 Data Analysis: Skilled in using tools like Python, SQL, Excel, and Power BI to explore data and extract actionable insights.
- 📊 Data Visualization: Creating clear and effective visualizations to communicate insights.
- 🔢 Statistical Foundation: Strong foundation in statistics for accurate analysis.
I'm on a continuous journey to enhance my data analysis skills.
I aim to transform raw data into actionable insights that help drive smarter business decisions.
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Zepto Inventory Zepto Inventory analyzes product sales, discounts, and stock levels to provide actionable business insights. It helps identify top-performing categories, out-of-stock items, and pricing opportunities, enabling data-driven decisions for improved sales and inventory management. |
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Airbnb NYC 2019 Dashboard To design an interactive Excel dashboard on the 2019 Airbnb New York City dataset that uncovers insights into pricing, availability, guest behavior, and host activity, with the goal of simplifying data exploration and supporting better decision-making through clear visualizations. |
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Diwali Sales Analysis This project explores and analyzes Diwali sales data to uncover consumer behavior insights, spending patterns, and regional trends during the festive season. It includes data cleaning, visualizations, and interpretation to support business decisions in marketing and sales strategy. |
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Employee Analytics Dashboard A complete end-to-end data analytics project where I cleaned and analyzed employee data using Python, Excel (Power Query), PostgreSQL, and Power BI. This project uncovers key business insights such as salary distribution, department-wise performance, work type trends, and hiring patterns. |
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Netflix Users Analysis This project explores and visualizes Netflix users data to understand user behavior, subscription preferences, and content interests. The analysis was performed using Python with Pandas, NumPy, Matplotlib, and Seaborn. |
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Cafe Sales Cleaned a messy cafe sales dataset using Pandas. Visualized trends with Matplotlib & Seaborn. Created monthly insights, fixed data types, and handled missing values. |
If you share a love for data, analytics, or problem-solving, or if you’d like to collaborate on exciting projects, I’d be glad to connect.
📩 Feel free to reach out to me at gauravxv0410@gmail.com
let’s create something impactful together!