📈 Data Analysis & Visualisation Portfolio Microsoft Excel  

This README provides an overview of the Excel-based data analysis projects contained within this repository.

Project 1: Retail Sales Analysis & Function Application

retail_sales_dataset.xlsx

Objective: Analysed retail sales data to uncover patterns and demonstrate core Excel data handling, formula application, and summarisation skills.

Key Activities & Skills Demonstrated:

• Data Structuring & Initial Cleaning: Organised raw data into Excel Tables; Applied Filters and Sorting (e.g., sorting customers by Age).
• Core Calculations & Logic: Calculated metrics using SUM and AVERAGE (e.g., commissions); Used SWITCH with AND logic for categorisation (e.g., sales volume tiers).
• Data Retrieval & Joining (Deeper Dive): (User mentioned - include if applicable) Leveraged VLOOKUP / XLOOKUP to integrate data; Used CONCATENATE (or &) for combining text fields.
• Summarisation with Pivot Tables: Created Pivot Tables to aggregate sales data across dimensions (Product Category, Customer Generation, Gender).

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Project 2: Student Performance Analysis

students.xlsx

Objective: Analysed student scores to identify top performers and demonstrate targeted formula application and conditional formatting.

Key Activities & Skills Demonstrated:

• Performance Calculation: Used AVERAGE to calculate overall student scores.
• Identifying Top Scores: Applied the MAX function to find the highest scores overall.
• Advanced Filtering/Formula: Used Filters & Sorting and advanced formulas (like FILTER, TEXTJOIN as shown in workbook examples) to identify top students per subject.
• Visual Highlighting: Employed Conditional Formatting to visually distinguish highest and lowest average scores.

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Project 3: Tech Shop Data Analysis

tech_shop.xlsx

Objective: Analysed tech shop sales data for various English counties, summarising performance and categorising sales volume using logical functions.

Key Activities & Skills Demonstrated:

• Created Pivot Tables to summarise sales volume by County and Product.
• Applied the SWITCH function, incorporating AND logic, to accurately categorise sales volume into "High", "Medium", and "Low" tiers based on specified thresholds.

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Project 4: Bike Sales Performance & Visualisation

bike_sales.xlsx

Objective: Analysed detailed bike sales data to understand profitability drivers and market performance, then visualised key findings effectively.

Key Activities & Skills Demonstrated:

• Advanced Pivot Table Analysis: Built Pivot Tables for multi-dimensional analysis (Profit/Sales by Age Group, Gender, Country); Cleaned data within analysis (TRIM, PROPER); Used functions (COUNTA, IF, MAX) with Pivot Table results for deeper insights; Applied Conditional Formatting to highlight key Pivot Table results.
• Data Visualisation for Impact: Created and formatted Line Charts (Revenue vs. Profit trends), Stacked Column Charts (Product Revenue by Country), and Pie Charts (Revenue by Age Group); Applied best-practice Chart Formatting (titles, labels, legends, number formats).

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Summary of Key Excel Skills Demonstrated:

• Data Prep & Handling: Tables, Filtering, Sorting, Cleaning Functions (TRIM, PROPER).
• Formulas & Logic: SUM, AVERAGE, MAX, IF, SWITCH, AND, COUNTA, VLOOKUP/XLOOKUP, CONCATENATE, FILTER, TEXTJOIN).
• Analysis Engine: Pivot Tables for multi-dimensional summaries and insights.
• Visualisation: Creating and refining Line Charts, Column Charts, and Pie Charts for clear communication.
• Presentation: Conditional Formatting, logical workbook structure.

📊 Example Output

Excel_Workbook

🧑‍💻 Created by tunjis

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