Excel Data Analysis Project Page📊
Excel Data Analysis Project Page📊
Welcome to my Excel project page! Were i used Microsoft Excel to analyse retail and sales data, applying formulas, PivotTables, filtering, sorting and charts to identify trends and generate meaningful insights. This project helped me develop practical skills in data analysis and visualisation. 📊📈Â
I analysed 1,000 retail transactions using Excel to explore sales performance, customer demographics and product categories. The analysis used formulas, filtering, sorting and visualisations to identify patterns across Clothing, Electronics and Beauty sales.
The dataset contains 1,000 transactions, with Clothing representing the largest category by number of transactions. I also analysed total sales, quantity, customer age and commission to understand overall retail performance.
📈 Visualisation: Charts were used to make the results easier to interpret, highlight differences between product categories and communicate key findings clearly. You can find this project on my GitHub, Retail Sales Data Analysis & Visualisation
📊 Bike Sales Analysis & VisualisationÂ
I analysed bike sales data using Excel to explore customer demographics, products, sales performance and profitability. The analysis included 96 sales records across different countries, customer age groups, genders and product categories.
📈 Visualisation: Charts and PivotTables were used to compare revenue, profit, products and customer groups, making it easier to identify patterns and differences in sales performance.
🔎 Data Analysis: I used Excel to summarise sales data by country, age group, gender and product, helping to identify which areas and customer groups contributed to overall performance. You can find this project on my GitHub, Bike Sales Data Analysis & VisualisationÂ
I analysed Human Resources data using Excel to explore employee headcount, salaries, departments and payroll information.
📊 The analysis focused on comparing salary levels and employee distribution across departments, helping to identify patterns within the workforce.
📈 Visualisation: Charts were used to present HR information clearly, making it easier to compare employee numbers and salary data.
🔎 Data Analysis: I worked with employee records containing information such as name, sex, salary and department, alongside payroll rules and calculations.
💡 Key focus: Turning HR and payroll data into clear visual insights that can support workforce planning and data-driven business decisions.