Portfolio - Kori Ganesh | Codebasics

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Kori Ganesh

Data Analyst

EMAIL

[email protected]

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About Me

I’m a Data Analyst focused on turning data into clear, actionable insights. I’ve developed strong skills in SQL, Python, Power BI, and Excel, using them to clean, analyze, and visualize data to understand business performance and customer behavior.

I’ve worked on several hands-on projects across hospitality, consumer electronics, and online retail, analyzing revenue trends, product performance, and customer activity to uncover meaningful patterns. All of my projects are showcased in the portfolio below.

I’m excited to contribute in a data-driven environment where analytical thinking and clear storytelling with data help drive smarter decisions.

1

Excel Project

1

PowerBI Project

1

SQL Project

1

Python Project

Key Skills

SQL

PYTHON

MS EXCEL

POWER BI

My Projects

Awards & Certificate

Excel: Mother of Business Intelligence

Get Job Ready: Power BI Data Analytics for All Levels 3.0

SQL Beginner to Advanced For Data Professionals

Let's Work Together!

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

EMAIL

[email protected]

LinkedIn

https://www.linkedin.com/in/kori-ganesh/

GitHub

https://github.com/kori-ganesh

Excel Project

Sales Analytics

Domain/Function: FMCG

Created 2 reports for the sales team which will help them to evaluate customer performance and understand their market performance with respect to their target.

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Engagement

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on GitHUB

Sales Analytics

Customer Performance Report: Provides net sales performance of each customer across years

Sales Analytics

Market performance vs Target report across years: Enables stakeholders to assess the country's performance and compare it to set targets.

Project Details

In this project, I created a sales report using Excel pivot tables which will enable businesses to determine effective customer discounts, facilitate negotiations with consumers, and identify potential business expansion opportunities in promising countries. The reports generated will provide actionable insights and recommendations for businesses to optimize their sales strategies, enhance customer satisfaction, and maximize revenue generation.

I have learned the following:

1. Pivot table
2. Power Query
3. DAX (Basics)
4. Conditional Formatting
5. Report Beautification
6. Sales Domain Metrics
7. Establishing data model relationships with Power Pivot.

Overall, this project aims to empower businesses with the necessary tools and insights to monitor, evaluate, and enhance their sales activities. By leveraging sales data analysis, businesses can unlock new opportunities, drive growth, and stay competitive in the dynamic market landscape.

PowerBI Project

Business Insights 360

Domain/Function: FMCG

Atliq Hardwares is expanding quickly but struggles to compete due to Excel-based reporting. I developed a Power BI analytics solution that transforms their data into actionable insights for faster, informed decision-making.

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Engagement

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on GitHUB

Business Insights 360

User-empathetic landing page as a part of dashboard design

Business Insights 360

Executive view offering CEO-level insights for strategic, company-wide decision-making.

Project Details

I developed a full-scale Power BI analytics solution for Atliq Hardware as part of the BI360 case study. The project transformed 1.4M+ rows of sales, finance, marketing, and supply-chain data into an interactive, executive-ready dashboard. Using Power Query, and DAX, I cleaned the data, built a star schema model, and designed five views—Finance, Sales, Marketing, Supply Chain, and Executive—featuring KPIs, field parameters, bookmarks, dynamic titles, and custom tooltips.

The dashboard reveals key insights such as GM% performance, revenue drivers, customer and product trends, market growth opportunities, and forecast accuracy gaps. These insights support better decision-making across functions and demonstrate my ability to convert raw data into actionable business intelligence.

Project video

Live Interactive Dashboard

SQL Project

Consumer Goods Business Insights

Domain/Function: Consumer Hardware

Performed SQL analysis on 1M+ consumer goods sales records to solve business questions around product portfolio performance, discount strategy, and seasonal sales trends, generating insights for faster decision-making.

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Engagement

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on GitHUB

Consumer Goods Business Insights

segment wise product count

Consumer Goods Business Insights

Bar chart showing gross sales by quarters

Project Details

AtliQ Hardwares, a consumer hardware manufacturer, lacked timely insights to support quick data-driven decisions. Management needed visibility into product performance, pricing strategy, and sales trends to understand where growth opportunities and operational risks existed.

To address this, I analyzed 1M+ sales records across multiple tables using SQL (joins, CTEs, window functions) to answer business questions on product portfolio performance, customer discounts, and seasonal sales patterns. The analysis revealed SKU efficiency gaps (Accessories: 116 SKUs generating $1.07B vs Peripherals: 84 SKUs generating $1.39B) and uniform 29–31% discounts for top customers, highlighting pricing risks and opportunities for improved product and pricing strategies.

Python Project

Online Retail Customer Analysis

Domain/Function: E-commerce Retail

Analyzed 500K+ online retail transactions using Python to study customer purchasing behavior and revenue concentration, revealing 84.6% of revenue from one country and defining a 90-day inactivity threshold for churn risk.

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Engagement

View Project
on GitHUB

Online Retail Customer Analysis

Customer churn analysis using recency data to flag inactive users beyond a 90-day threshold.

Online Retail Customer Analysis

Top 5 countries revenue contribution by percentage using a Horizontal Bar Chart.

Project Details

An online retail company needed better visibility into customer purchasing behavior and revenue distribution to support data-driven decision-making. However, the large volume of transaction data made it difficult to identify patterns in customer activity, revenue concentration, and potential churn risks.

To address this, I analyzed 500K+ transaction records using Python (Pandas) to study customer purchase behavior and revenue distribution. The analysis revealed that 84.6% of revenue came from a single country and helped define a 90-day inactivity threshold to identify churn risk, highlighting opportunities for geographic diversification and targeted customer retention strategies.