KUNAL DAGAR

Data Aspirant

[email protected] +91 9315005650

Resume

Hello, I am

KUNAL DAGAR.

1

Excel
Project

3

PowerBI
Projects

1

SQL
Project

1

Python
Project

About Me

I'm a passionate Data Analyst eager to turn raw data into actionable insights. With a strong foundation in Python, SQL, Power BI, and Excel, I specialize in data preprocessing, analysis, and visualization. My experience includes developing machine learning models, conducting exploratory data analysis, and creating insightful dashboards. I've worked on projects like EV market analysis, store sales analysis, and a book recommendation system, showcasing my ability to deliver data-driven solutions. Skilled in tools like Tableau and Informatica, I aim to leverage my analytical mindset to help businesses make informed decisions and drive growth.

Key Skills

Python

Power BI

SQL

Machine Learning

Advance Excel

My Projects

Business Insights 360

Domain/Function: Retail Analysis

EV Market Analysis

Domain/Function: Retail Analysis (EV)

KPMG Data Analysis

Domain/Function: Retail Analysis

Airline Data Analysis

Domain/Function: Airline

Walmart Data Analysis Using SQL

Domain/Function: Sales Analysis

Electric vehicle Data Analysis

Domain/Function: EV Analysis

My Experience

Coforge (June 2024 – October 2024)

Worked on projects leveraging Python and Generative AI, developing innovative solutions for content generation and automation.
Built and fine-tuned Generative AI models for tasks like text summarization and predictive analysis, improving operational efficiency.
Enhanced data workflows by integrating AI capabilities, enabling smarter decision-making and automation.
Collaborated with cross-functional teams to deliver AI-driven tools, ensuring impactful and scalable results.

Bolt IoT (January 2024 – June 2024)

Served as a Software Development Intern, specializing in Python and data preprocessing to enhance data quality and integrity.
Conducted Exploratory Data Analysis (EDA), uncovering insights to drive informed decisions and improve machine learning model accuracy beyond 90%.
Developed and deployed machine learning models and contributed to web designing projects, creating user-friendly and scalable solutions.
Applied advanced data processing methodologies, optimizing workflows for robust modeling and analysis.

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

Python : Certificate of Excellance

Let's Connect

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.

Mail Me

[email protected]

https://www.linkedin.com/in/kunal-dagar-30a306210/

Call Me

+91 9315005650

GitHub

https://github.com/KUNAL-DAGAR-2002

PowerBI Project

Business Insights 360

Domain/Function: Retail Analysis

Created a data analytics solution managing 1.8M+ records across 8 segments, boosting efficiency by 25%. Enhanced customer retention by 15% through segmentation and delivered actionable insights from sales trends and behavior analysis, driving revenue growth and strategic decisions.

Finance view displays P&L, net sales, gross margin, and YOY % across segments and regions.

Supply chain view highlights forecast accuracy, tracking the precision of predictions.

Project Details

Engineered a robust data analytics solution that revolutionized cumbersome Excel files, achieving a 25% boost in business efficiency by adeptly managing and analyzing over 1.8 million records across 8 segments and 25+ countries.
Executed strategic segmentation to precisely target high-value customer groups, driving a 15% increase in customer retention through actionable insights that pinpointed profitable customers and optimized gross margins.
Unveiled critical insights by performing comprehensive analysis of sales spikes and customer behavior patterns, empowering the business to craft data-driven strategies that significantly elevated revenue growth and enhanced overall operational efficiency.

Live Interactive Dashboard

PowerBI Project

EV Market Analysis

Domain/Function: Retail Analysis (EV)

Led the EV market analysis for AtliQ Motors, analyzing 2,000+ rows of data. Developed a dashboard showcasing ₹2.24 trillion revenue, with insights on customer behavior, top states, and sales growth, driving strategic decisions for market entry and brand positioning.

Sales view displays net sales and penetration rate across segments and regions, tracking revenue, growth rate, and market share,

Maker sales view analyzes top makers, sales, revenue generation, and market share.

Project Details

Spearheaded the project to equip AtliQ Motors with essential insights into the electric vehicle (EV) market in India, tackling challenges related to limited market share by meticulously collecting and cleaning data from a dataset of over 2,000 rows.
Conducted comprehensive data modeling and analysis, employing trend analysis and segmentation techniques to reveal customer behavior and preferences. This analysis directly informed the creation of the EV Market Analysis Dashboard, showcasing a total revenue of ₹2.24 trillion—₹1.48 trillion from 2-wheelers and ₹0.76 trillion from 4-wheelers.
Delivered actionable insights that influenced strategic market entry decisions, identifying top-performing states like Maharashtra and illustrating a significant upward sales trend from 2021 to 2024, ultimately amplifying potential sales and strengthening brand positioning in an expanding market.

Live Interactive Dashboard

Excel Project

KPMG Data Analysis

Domain/Function: Retail Analysis

Executed a comprehensive data analysis project on the KPMG dataset using Excel. Conducted customer segmentation, transaction analysis, and CLV analysis to uncover trends, customer behaviors, and performance metrics, providing a foundation for data-driven decision-making.

View Project
on GitHUB

View Project
on

Display the regional distribution of new customers across different areas in Australia.

Show customer distribution across job industries, categorized further by wealth segments.

Project Details

Utilized Excel to analyze the KPMG dataset, focusing on customer segmentation, transaction patterns, and customer lifetime value (CLV). The project involved detailed exploration of customer demographics, industry-wise distribution, and sales performance. Insights were derived by examining customer behavior, revenue contributions, and CLV breakdowns across various segments. The analysis provided valuable information to support strategic decision-making and improve customer engagement strategies.

PowerBI Project

Airline Data Analysis

Domain/Function: Airline

Streamlined data cleaning to ensure accuracy across flight schedules, passenger details, and ticketing systems. Designed an interactive Power BI dashboard for real-time insights, configured automated refresh schedules, and hosted it on Power BI Service to enable informed decision making.

View Project
on GitHUB

Dashboard for airline specific analysis.

Visualizations for checking percentage distribution of booking status across various categories.

Project Details

This Power BI dashboard provides an in-depth analysis of airline operations, focusing on key metrics such as passenger count, ticket booking statuses, and flight performance across destinations. It enables users to track booking trends, analyze flight statuses, and gain insights into passenger travel patterns with each airline. Interactive features like dynamic filtering by airline and destination allow for detailed analysis, empowering users to drill down into specific data. Designed to support strategic planning, the dashboard helps improve customer insights, optimize flight schedules, and enhance operational efficiency. By delivering actionable insights, it enables airlines to identify bottlenecks, streamline processes, and make data-driven decisions that boost performance and customer satisfaction. This tool is essential for effective airline management.

Project video

SQL Project

Walmart Data Analysis Using SQL

Domain/Function: Sales Analysis

Analyzed Walmart's sales data using advanced SQL to uncover actionable insights into sales performance, customer behavior, and operational efficiencies. Tasks included identifying top-performing branches, analyzing customer spending tiers, and detecting sales anomalies.

View Project
on GitHUB

View Project
on

Table showing total sales per day in a week

Graph showing Total Sales per customer

Project Details

This project aimed to optimize Walmart's sales strategies by analyzing historical transaction data across branches, customer types, payment methods, and product lines using advanced SQL techniques. Key tasks included identifying the branch with the highest sales growth, determining the most profitable product lines by branch, and segmenting customers based on spending behavior. Anomalies in sales transactions were detected to ensure data integrity. The project also analyzed the popularity of payment methods by city, monthly sales distribution by gender, and preferred product lines by customer type. Repeat customers were identified within a 30-day timeframe, and the top 5 customers by sales revenue were recognized for potential rewards. Additionally, sales trends by day of the week were examined to optimize operational efficiencies and marketing strategies.

Project video

Python Project

Electric vehicle Data Analysis

Domain/Function: EV Analysis

Analyzed an EV dataset using Python libraries to uncover insights. Filtered EVs by budget and range, grouped by manufacturer, calculated average battery capacities, identified energy consumption outliers, visualized battery-range correlation, and performed hypothesis testing.

View Project
on GitHUB

View Project
on Python, VS Code

Plot to check outlier in given column

Plot showing correlation between battery capacity and range.

Project Details

This project analyzes an electric vehicle (EV) dataset with features like price, battery capacity, and energy consumption to derive actionable insights. Tasks include filtering EVs based on a budget of 350,000 PLN and a range of 400 km, grouping them by manufacturer, and calculating average battery capacities. Outliers in energy consumption were identified, and a visualization of the relationship between battery capacity and range was created. Additionally, an EV recommendation system was built to suggest top options based on user inputs. Inferential statistics were applied through a two-sample t-test to examine differences in engine power between Tesla and Audi, providing actionable insights for strategic decisions.