Portfolio - Karankumar Hirapara

Excel Project

Excel reports for AtliQ Hardware's product performance analysis

Domain/Function: Sales

This project delivers advanced Excel reports for AtliQ Hardware's product performance analysis, focusing on sales and market insights.This will help Atliq in decision making.

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Excel reports for AtliQ Hardware's product performance analysis

Tracking success of new launches Market penetration insights

Year-over-year growth percentages Performance visualization across different segments

Project Details

The AtliQ Hardware Sales Analysis project generated interactive reports comparing product performance and sales growth from 2020 to 2021. Key features include filtering capabilities, advanced Excel formulas, and user-friendly interfaces. The analysis revealed significant growth across divisions, with PC sales increasing from $40.1 million to $165.8 million, and accessories sales growing 321.5% to $338.4 million. The project utilized ETL methodology, Power Query, Power Pivot, and DAX for data processing and visualization. These reports provide valuable insights into product performance, market trends, and financial metrics, empowering AtliQ Hardware to make data-driven decisions and optimize sales strategies across regions and customer segments.

PowerBI Project

Power BI 360: Comprehensive Business Intelligence Dashboard

Domain/Function: Business intelligence

This project presents a comprehensive 360-degree view of business operations using Power BI. The dashboard encompasses multiple aspects of the organization, including Finance, Sales, Marketing, Supply Chain, and Executive insights.

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Power BI 360: Comprehensive Business Intelligence Dashboard

Financial dashboard with advance KPI and advance graph which shows callout value on graph.

Advance Executive view.

Project Details

This Power BI project offers a comprehensive business overview with intuitive navigation across Finance, Sales, Marketing, Supply Chain, and Executive views. It features advanced KPIs, interactive visualizations, and detailed analyses for data-driven decision-making. With customizable filters and in-depth metrics explanations, it caters to various stakeholders. The dashboard combines financial, sales, marketing, and supply chain insights into a user-friendly interface, showcasing advanced Power BI techniques and cross-view consistency.

Live Interactive Dashboard

SQL Project

Inden Bank Database Management System

Domain/Function: BANK

This project implements a comprehensive Database Management System (DBMS) for Inden Bank using MySQL. The system is designed to efficiently manage financial data, client information, transactions, and services, ensuring seamless operations and superior customer experiences.

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ERD visualizes relationships between key entities: Branches, Products/Services, Clients, Accounts, and Transactions in the banking system.

SQL query using GROUP BY demonstrates aggregating data by branch ID to analyze account balances or transaction patterns across branches.

Project Details

This project presents a comprehensive DBMS solution for Inden Bank, featuring:

- ERD with key entities: Branches, Products/Services, Clients, Accounts, Transactions
- Database schema with 5 main tables
- 8 SQL queries demonstrating various operations
- Stored procedure for transaction management

Key focus areas:
- Data integrity and reliability
- Efficient retrieval and scalability
- Security and regulatory compliance
- ACID properties adherence
- CAP theorem application

The solution emphasizes robust transaction handling, data relationships, and system performance, providing a solid foundation for the bank's operational needs while addressing crucial aspects of financial data management.

Python Project

Personalized Ad Targeting System

Domain/Function: Marketing

This project develops a cutting-edge personalized ad targeting system for a high-traffic website, leveraging customer data to enhance engagement and boost conversion rates.

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on Colab

Visualized customer age distribution using Matplotlib to gain insights into demographic patterns and inform targeting strategies.

Model Evaluation: Assessed model performance using accuracy scores and F1 metrics to compare Logistic Regression and Random Forest algorithms.

Project Details

Ad Targeting System

Key features:
- Data collection from cookies
- Preprocessing with Python/Pandas
- EDA using Matplotlib
- ML models: Logistic Regression, Random Forest
- Real-time personalized ad display

Technologies: Python, Pandas, Matplotlib, Scikit-learn

Results:
- Improved customer engagement
- Increased conversion rates
- Enhanced user experience

Future plans:
- Real-time targeting
- Continuous model improvement
- Expanded feature set

Usage:
1. Clone repo
2. Install dependencies: `pip install -r requirements.txt`
3. Run: `python ad_targeting.py`

Contributions welcome. MIT License.

Acknowledgments:
- Kaggle for dataset
- Open-source community

This project demonstrates data analytics in marketing, applying ML to create personalized advertising strategies.

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Karankumar Hirapara

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Excel reports for AtliQ Hardware's product performance analysis

Power BI 360: Comprehensive Business Intelligence Dashboard

Inden Bank Database Management System

Personalized Ad Targeting System

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Karankumar Hirapara