Projects

Project 1:  UK Property Price Analytics Dashboard

Tools:

• Streamlit

• Python

• Pandas

Problem:
Analyze long-term UK housing market trends.

Dataset:
UK Property Data (2010–2026)

What I Did:

• Cleaned and transformed housing data.

• Built interactive filters.

• Developed visualizations for trend analysis.

• Created a dashboard for investment insights.

Key Insights:

• Property prices showed long-term growth trends.

• Regional differences created varying investment opportunities.

Project 2:  UK Real Estate Market Intelligence Dashboard

Tools:

Power BI

Problem:
Provide business intelligence insights into the UK property market performance.

What I Did:

• Developed a KPI dashboard.

• Built trend visualizations.

• Analyzed transaction activity.

• Compared market performance across property categories.

Key Insights:

• Identified regional pricing differences.

• Highlighted transaction activity patterns.

Project 3: Retail Sales Performance Analysis

Tools:

• MySQL

• SQL

Problem:
Analyze retail transaction data to identify revenue drivers, customer spending patterns, and business performance across branches.

Dataset:
Retail Sales Dataset (Transactions, Customers, Products)

What I Did:

• Queried and analyzed transactional sales data using SQL.

• Performed joins across multiple tables to combine customer, product, and sales information.

• Used aggregate functions, subqueries, and CASE statements to answer key business questions.

• Segmented transactions into spending bands and identified top-performing customers and products.

Key Insights:

• Certain product categories generated significantly higher revenue than others.

• Customer spending analysis revealed high-value customers suitable for loyalty programs.

• Revenue varied across branches, highlighting opportunities for performance improvement.

Project 4: Retrieval-Augmented Generation (RAG) Research System

Tools:

Python

AI Tools

Problem:
Improve AI response quality using external knowledge retrieval.

What I Did:

Built retrieval workflows.

Integrated contextual knowledge sources.

Improved information relevance.

Project 5: University Student Performance Analysis

Tools:

• MySQL

• SQL

Problem:
Analyze student academic performance to identify trends, high-performing students, and departmental performance.

Dataset:
University Student Records Dataset

What I Did:

• Queried student performance data using SQL.

• Applied aggregate functions to evaluate GPA trends across departments and genders.

• Used joins to analyze course registration patterns.

• Identified students who had not registered for courses and evaluated overall academic performance.

Key Insights:

• Academic performance varied across departments and demographic groups.

• Several students had not completed course registration, indicating possible administrative gaps.

• Performance analysis identified top-performing students and departments.

Project 6:  Business Analytics Solutions

Tools: Google Sheets, Pivot Tables, Charts, Formulas, Conditional Formatting, Dashboard Design

Projects Included

• Sales Analysis Dashboard
• Expense Tracker
• Payroll Management System
• Inventory Management System
• Student Performance Dashboard

Problem

Many small businesses and organizations struggle with scattered data, manual reporting processes, and limited visibility into operational performance. These solutions were developed to organize data, automate calculations, improve reporting accuracy, and support informed decision-making.

What I Did

• Designed and developed five Excel-based analytical solutions for business and operational reporting.

• Built automated calculations using Excel formulas and functions to reduce manual effort.

• Created interactive dashboards and visual reports using charts, Pivot Tables, and conditional formatting.

• Structured datasets for easier tracking, monitoring, and performance analysis.

• Developed reporting systems for sales, expenses, payroll, inventory, and student performance management.

Key Insights

• Enabled faster access to business performance metrics through dashboard-driven reporting.

• Improved visibility into sales trends, expense patterns, inventory levels, payroll records, and academic performance.

• Demonstrated how Excel can be used as a practical business intelligence tool for analysis and decision support.

• Showcased skills in data organization, reporting automation, visualization, and analytical problem-solving.