Yeshwanth Reddy

About

Computer Science undergraduate with hands-on experience in SQL, Python, PostgreSQL, Power BI, Tableau, and Excel through analytics and database projects. Skilled in data cleaning, relational database management, dashboard development, and KPI reporting to deliver actionable business insights.

Experience

• Data Analytics Job Simulation
  Forage
  Aug 2026 – 2026
• Data Visualisation: Empowering Business with Effective Insights
  Forage
  Aug 2026 – 2026

Education

• B.Tech in Computer Science and Engineering
  Amrita Vishwa Vidyapeetham
  Computer Science and Engineering · 2023 – 2027
• Qualification
  Narayana Junior College
  2021 – 2023

Skills

• C
• Data Engineering
• Python
• Data Cleaning
• NumPy
• Pandas
• PySpark
• Dashboard Development
• Statistical Analysis
• Exploratory Data Analysis
• KPI reporting

Projects

• E-Commerce Sales & Customer Analytics
  PostgreSQL, SQL, Python, Pandas, Power BI

  Designed and implemented a relational PostgreSQL database using the Olist e-commerce dataset, integrating customer, order, product, seller, payment, review, and geolocation data for end-to-end sales analysis. Developed SQL queries using multi-table joins, CTEs, aggregate functions, and window functions to analyze revenue, delivery performance, repeat purchases, and customer behavior. Performed RFM-based customer segmentation and analyzed the relationship between delivery delays and review scores, presenting KPIs and business insights through an interactive Power BI dashboard.

• Sales Data Analysis & Business Insights Dashboard
  Python, Pandas, NumPy, SQL, Power BI

  Cleaned and transformed sales datasets using Python/Pandas and SQL to improve data quality and prepare for business analysis. Built interactive Power BI dashboards to track KPIs, sales trends, customer segments, and product performance, generating actionable business insights. Analyzed revenue, customer, and product performance trends to identify key business drivers and support data-driven decision-making.

• Marketing Campaign Performance Analysis
  Python, Pandas, NumPy, SQL, Power BI

  Cleaned and transformed digital marketing datasets using Python/Pandas and SQL for campaign performance analysis. Developed Power BI dashboards to analyze campaign KPIs, conversion rates, customer acquisition, channel performance, and ROI, identifying high-performing marketing channels. Compared campaign performance across channels and customer segments to identify high-performing strategies and opportunities for improving ROI.