My name is Abhishek, I'm an entry-level Data Analyst with a Bachelor's degree in Computer Applications, during which I've developed foundations in programming and problem solving. I'm passionate about transforming raw data into innovative, actionable insights that drive smart decision making. Through these personal and academic projects, I've gained knowledge in data cleaning, visualization and exploratory analysis using tools like Python, SQL, Excel and PowerBI. Allowing me to uncover patterns and build dashboards that tell stories.
Exploratory analysis of 3 decades of UFC fight data, enhanced with additional columns such as height/reach/age differences and performance differentials. The project examines trends in fight volume, title vs. non-title bouts, fighter attributes, win methods, and performance metrics. All insights were summarized using Excel pivot tables and visualizations.
This project highlights how fighter attributes and performance metrics relate to win probability, reveals long-term trends in win methods and submission types, and shows how outcomes vary across weight classes. It also serves as a foundation for future predictive modelling.
Excel (data cleaning, feature engineering, pivot tables, visualizations)
An end-to-end analytics project using a hypothetical retail dataset for a fictional electronics store called TechPoint. SQL was used to calculate KPIs and metrics, followed by a detailed Power BI dashboard and Python visualizations in Colab. The analysis covers sales patterns across item types, power usage categories, outlet characteristics, and establishment years.
The project reveals which item types and outlet attributes drive the most revenue, how power usage correlates with sales, and how performance varies by outlet size, type, and location. The Cross-validation across SQL, Power BI, and Python ensures consistency.
SQL, Power BI, Python (pandas, matplotlib, seaborn), Excel, Google Colab
A sales analysis project for a hypothetical coffee shop using SQL for calculating KPIs and other metrics, and Excel for a detailed dashboard. The project examines daily and hourly order patterns, sales distribution across drink categories and sizes, and best/worst selling products.
This analysis identifies peak business hours and days, top-performing drink types, underperforming drinks, and identifies patterns that can support inventory and menu improvements. SQL generated insights combined with Excel dashboards provides clear, actionable insights.
SQL, Excel (Pivot Tables, Charts, Timelines, Slicers)
Amrita Vishwa Vidyapeetham: Bachelor of Computer Applications June 2022 - October 2025
- Microsoft Python Development (Coursera - Microsoft)
- Google Cloud Computing Foundations (Google Skills - Google)
- Generative AI Automation (Coursera - Vanderbilt University)
- Email: [email protected]
- Linkedin: Abhishek Ganesh