Portfolio - SREE VIGNESH S | Codebasics

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SREE VIGNESH S

Data Analyst

EMAIL

[email protected]

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About Me

I’m a Microsoft Certified Power BI Data Analyst Associate with a passion for transforming data into meaningful insights. I’ve built strong skills in Excel, Power BI, SQL, and Python, using them to make sense of complex data and deliver clear, actionable solutions.

I’ve completed several business-focused data projects that highlight my ability to analyze trends, solve problems, and support decision-making — all showcased in my portfolio below.

While I’m just starting my professional journey, I’m eager to join a team where I can continue learning, contribute with impact, and grow as a data professional.

1

Excel Project

2

PowerBI Projects

2

SQL Projects

1

Python Project

Key Skills

SQL

Excel

Power BI

Python - Pandas

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

SQL INTERMEDIATE

SQL INTERMEDIATE

Power BI Service

Power BI Service

PL 300 Exam Preparation

PL 300 Exam Preparation

Advanced SQL

Microsoft Certified Power BI Data Analyst Associate

Microsoft Certified Power BI Data Analyst Associate

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/sree-vignesh-05-/

GitHub

https://github.com/sreevignesh05

PowerBI Project

Performance analysis - Good Cabs

Domain/Function: Transportation and Mobility

This project analyzes and enhances Goodcabs' operations in tier-2 cities across India, focusing on key metrics like trip volume, passenger satisfaction, and fare efficiency to improve service delivery and growth.

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Engagement

View Project
on GitHUB

Other Tools

SQL

Performance analysis - Good Cabs

The General Insights page highlights key metrics and trends, offering data-driven insights to guide business decisions and improve performance.

Performance analysis - Good Cabs

The Target vs Actuals page compares performance against set goals, highlighting deviations and identifying areas for improvement.

Project Details

This project analyzes and enhances Goodcabs' operations, targeting tier-2 cities across India, with a focus on improving service efficiency and expanding customer reach.

Key Focus Areas:

1. Boosting trip volumes in cities like Mysore, Coimbatore, and Vadodara.
2. Optimizing pricing strategies for high- and low-revenue cities.
3. Demand-based driver allocation to align with city dynamics.
4. Introducing Electric Vehicles (EVs) to reduce operational costs and appeal to eco-conscious passengers.
5. Collaborating with partners such as malls and hotels to expand the customer base.
6. Gathering more data for deeper insights into passenger and driver behavior.

Key Recommendations:

• Launch targeted campaigns and loyalty programs to increase trip volumes.
• Adjust pricing and service strategies based on city-specific trends.
• Optimize driver allocation by leveraging demand-based data insights.

Project video

Live Interactive Dashboard

SQL Project

Executive Management - AdHoc analysis

Domain/Function: CG- Consumer Goods

I used SQL to dive into complex datasets and uncover key insights through ad-hoc analysis. Then, I brought those insights to life with clear and engaging visualizations using Python.

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Engagement

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on GitHUB

Other Tools

PYTHON

Executive Management - AdHoc analysis

Query to get the top 3 products in each division with the highest total_sold_quantity in fiscal year 2021.

Executive Management - AdHoc analysis

Python: Matplotlib visualization for the top 3 products in each division.

Project Details

In this project, I used SQL to dive into the data and perform ad-hoc analysis, ensuring the information was accurate and relevant. I worked on extracting key insights from complex datasets, helping business owners make better, quicker decisions.

I turned to Python for data visualization to make the findings easier to understand. Using libraries like Matplotlib and Seaborn, I created clear and impactful visualizations, making the insights more accessible and actionable for everyone involved.

What I Learned:

• How to perform ad-hoc analysis and extract data using SQL.
• Creating engaging data visualizations with Python (Matplotlib, Seaborn).
• Streamlining data processes for better efficiency.
• Using visual storytelling to communicate insights more clearly.
• Presenting complex data in a way that simplifies decision-making.

Impact:
This project improved data analysis efficiency and empowered stakeholders to make informed, data-driven decisions with clarity.

Project video

PowerBI Project

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

Domain/Function: FMCG

AtliQ Hardware is a consumer electronics company expanding rapidly but is not able to compete with other companies using data. My goal is to implement an advanced analytics solution using Power BI that will enable the company to make data-informed decisions.

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Engagement

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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 create one report that 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
10. Merging and Appending
11. Automatic data refresh using PBI service

Project video

Live Interactive Dashboard

Python Project

Descriptive Analytics for Atliq Grands

Domain/Function: Hospitality

The AtliQ Grand project analyzes sales, revenue, and customer trends to support decision-making. Key insights include peak sales periods, customer segmentation, and policy impact, enhancing profitability.

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on GitHUB

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on Python

Descriptive Analytics for Atliq Grands

This image shows the average occupancy rate by day type to identify whether weekdays or weekends have a higher occupancy percentage.

Descriptive Analytics for Atliq Grands

This image shows the city's total revenue (in millions) for conducting a city-level performance analysis.

Project Details

Overview :
This project analyzes data for AtliQ Grand to uncover insights into sales, revenue, and customer trends, supporting decision-making in the hospitality sector.

Objectives:

•Analyze revenue trends over time.
•Understand customer patterns based on demographics.
•Visualize sales, revenue, and customer segmentation.

Analysis Highlights:

•Sales Trends: Identified peak sales periods.
•Customer Segmentation: Grouped customers by age for targeted promotions.
•Revenue Insights: Analyzed revenue growth over time.
•Policy Impact: Examined how policy changes influenced business performance.

Key Findings:

•Identified months of high revenue growth and areas for operational improvement.

Conclusion:

The project provides actionable insights to enhance profitability and customer satisfaction.

Future Scope:

•Extend analysis to include customer feedback data.
•Implement dashboarding for real-time data visualization.

SQL Project

Ad-Hoc

Domain/Function: CPG

This project was focused on leveraging SQL to solve complex, real-time business problems through the use of ad-hoc queries and advanced database management techniques.

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Engagement

View Project
on GitHUB

This is a query to RANK markets in each region by their aggregated gross sales.

VIEWS - a virtual table to optimize the system performance and fetch the data faster.

Project Details

I utilized SQL queries to extract and analyze data, ensuring accuracy and relevance. I implemented stored procedures to streamline the process, automating repetitive tasks and enhancing efficiency. Additionally, I used views to improve query performance by simplifying complex data retrieval and ensuring faster execution. This combination of SQL techniques allowed for better data management and reporting.

I have learned the following:

1. Data retrieval using SQL queries.
2. Entity Relationship Diagram.
3. Extract, Transform, Load.
4. OLTP and OLAP.
5.SQL functions.
6. Creation of a Database.
7. SQL Data types.
8. Automation with stored procedures.
9. Streamlining data management
10. Kanban - Project Management Methodology.

Overall, this project aims to empower businesses with the necessary tools and insights to monitor, evaluate, and enhance their short-term goals. By leveraging data analysis, businesses can unlock new opportunities, drive growth, and stay competitive.

Project video

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

View Project
on GitHUB

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on

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.