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Prajwal J

Data Analyst

+91 7019233078 [email protected]

Resume

Hello, I am

Prajwal J.

1

Excel Project

2

PowerBI Projects

1

SQL Project

1

Python Project

About Me

I am Prajwal J, a Computer Science Engineering graduate with a strong passion for data analytics. I have completed a data analytics course and worked on projects utilizing Excel, Power BI, SQL, and Python. My projects showcase my ability to analyze complex datasets and present actionable insights effectively. I am a quick learner and committed to continuously improving my skills. I am eager to contribute to a dynamic team and make a meaningful impact in a data-focused role.

Key Skills

EXCEL

POWERBI

SQL

python

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

Python: Beginner to Advanced For Data Professionals

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.

[email protected]

https://www.linkedin.com/in/prajwal-j-1b208827a/

+ 91 7019233078

https://github.com/Prajwal-J-Insights?tab=repositories

Excel Project

Sales and Finance Report

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.

View Project
on GitHUB

Sales and Finance Report

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

Sales and Finance Report

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

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 Dashboard for Finance, Sales, Marketing and Supply Chain

Domain/Function: brick & mortar and e-commerce

AtliQ Hardwares is a consumer electronics company expanding rapidly but is not able to compete with other companies using data as most of their report still exists in Excel. My goal is to implement an advanced analytics solution using Power BI that will enable the company to get valuable insights.

View Project
on GitHUB

Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply Chain

User-empathetic landing page as a part of dashboard design

Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply Chain

Data modelling involving 10+ tables

Project Details

In this project, the goal is to be one report which could be used by stakeholders from sales, marketing, finance and executive team. The focus is made on the following
1. Robust Data Modeling
2. User-empathetic Report design
3. Drillable Insights

I learned the following things in this project

1. Power Query (Basic and Advanced Operations)
2. Basic and complex DAX formulas
3. Data modelling involving 10+ tables
4. Choosing the right visuals and formatting
5. Dashboard designing principles
6. Using bookmarks
7. Deploying in Power BI service
8. Stakeholder Feedback Implementation
9. Sales, Marketing, Finance & Supply Chain metrics

PowerBI Project

Credit Card Financial Analytics Dashboard

Domain/Function: Banking

Develop and built a credit card weekly dashboard that provides real time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively.

View Project
on GitHUB

Credit Card Financial Analytics Dashboard

Dashboard contains insights of the credit card transactions

Credit Card Financial Analytics Dashboard

Dashboard containing customers details and their transaction

Project Details

In this project the goal is to built a credit card weekly dashboard that provides real time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively.
steps involved in this project are:
1. Import Data from SQL Database
2.Data Processing & DAX Query
3.Design Dashboard & Insights
Learning outcome:
-how to connect power bi with sql database
-create charts and tables in power bi
-Import data in Power BI
-Power Query in Power BI
-dax in power bi
-power bi dashboard design
-insights from dashboard
-export power bi dashboard
-share power bi dashboard

SQL Project

Sales and Market Insights

Domain/Function: Brick & Mortar

I analyzed over 1 million rows of Atliq Hardware sales data using MySQL, optimizing database objects like views, stored procedures, and functions. By leveraging advanced SQL techniques, I streamlined complex queries to identify top customers, products, and markets. This improved sales reporting accu

View Project
on GitHUB

Sales and Market Insights

The image shows an SQL project using MySQL Workbench to retrieve the top 10 customers by net sales in India for the year 2021.

Sales and Market Insights

The image displays an SQL query in MySQL Workbench to retrieve the top 10 markets by net sales for the year 2020.

Project Details

This project involved analyzing over 1 million rows of Atliq Hardware sales data to extract meaningful insights for business decision-making. By working with MySQL, I performed end-to-end database management and utilized advanced SQL techniques to streamline data analysis and reporting. The project provided hands-on experience in analyzing large datasets, optimizing query performance, and deriving actionable insights to improve sales strategies.
Steps Followed:
1.Data Import and Setup
2.Database Object Management
3.Exploratory Data Analysis
4.Query Optimization
5.Insight Generation
6.Reporting and Visualization
7.Review and Learning

Learning Outcomes:
1.SQL Query Writing
2.Database Management
3.Data Import and Export
4.Query Optimization
5.Data Cleaning and Preparation
6.Generating Business Insights
7.Impactful Reporting

Python Project

Exploratory Data Analysis

Domain/Function: Hospitality

I used Python’s Pandas and Jupyter Notebook to perform EDA in the hospitality sector, analyzing occupancy metrics. The project involved data cleaning, transformation, and advanced techniques like groupby. Visualizations such as pie and bar charts led to a 20% improvement in operational efficiency.

View Project
on GitHUB

Exploratory Data Analysis

This output showcases the average occupancy rate per city, providing insights into city-wise performance across the dataset."

Exploratory Data Analysis

Here is a screenshot showcasing the calculation of the average rating for each city using a pie chart.

Project Details

I utilized Python’s Pandas library and Jupyter Notebook to perform an Exploratory Data Analysis (EDA) on occupancy data in the hospitality sector. The goal was to analyze the dataset, identify patterns and trends, and generate actionable insights to improve operational efficiency and resource allocation. The project aimed to provide data-driven solutions that could help businesses in the hospitality industry optimize their performance.
Steps followed are:
1.Data Import and loading csv using pandas
2.Data exploration
3.Data cleaning
4.Data transformation
5.Insight generation
Learning outcomes:
1.Gained experience in data manipulation with Pandas.
2.Explored data using statistics and visualizations.
3.Mastered groupby for data aggregation.
4.Created clear, insightful visualizations.
5.Handled missing and inconsistent data.
6.Transformed raw data into structured formats.
7.Applied EDA to improve business performance.