Hi, I’m Rishi Kesavan, a data analyst who turns raw data into actionable business insights. I specialize in SQL, Excel, Power BI, and Power Query, and I enjoy cleaning data, building robust data models, and designing KPI dashboards that drive decisions. I excel at exploratory data analysis to identify trends and opportunities, translating complex datasets into clear metrics and visual stories that support strategic planning.…

Rishi Kesavan

Hi, I’m Rishi Kesavan, a data analyst who turns raw data into actionable business insights. I specialize in SQL, Excel, Power BI, and Power Query, and I enjoy cleaning data, building robust data models, and designing KPI dashboards that drive decisions. I excel at exploratory data analysis to identify trends and opportunities, translating complex datasets into clear metrics and visual stories that support strategic planning.…

Available to hire

Hi, I’m Rishi Kesavan, a data analyst who turns raw data into actionable business insights. I specialize in SQL, Excel, Power BI, and Power Query, and I enjoy cleaning data, building robust data models, and designing KPI dashboards that drive decisions.

I excel at exploratory data analysis to identify trends and opportunities, translating complex datasets into clear metrics and visual stories that support strategic planning.

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Language

English
Advanced

Work Experience

Add your work experience history here.

Education

B.Tech in Information Technology at Misrimal Navajee Munoth Jain Engineering College, Affiliated to Anna University
November 22, 2021 - September 30, 2025

Qualifications

Deloitte Australia Data Analytics Job Simulation — Forage
January 1, 2026 - May 10, 2026
Certificate Course on Data Analytics — Infosys Foundation & ICT Academy
August 24, 2024 - September 30, 2024
Learnt the key steps of taking raw data, cleaning it, analysing it, and sharing dashboards with Power BI service
    paper Telco Customer Churn Analysis

    Analyzed 7,000+ telecom customers using SQL & Power BI to uncover a 26.5% churn rate, ~$3M in lost revenue, and $225K at risk. Identified key churn drivers, including month-to-month contracts (42.7%) and electronic check payments (45.3%), to support smarter retention decisions.

    paper Superstore Sales Performance Analysis

    Analyzed 9,994 retail orders spread across 4 years using SQL & Power BI to uncover $2.3M in revenue and $286K in profit — while identifying $213K in avoidable losses driven by over-discounting, returns, and unprofitable products. Turned four years of raw sales data into clear business decisions.

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