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Chocolate Factory Analysis

Project Overview

This project presents a comprehensive sales analytics dashboard for a chocolate manufacturing company. The dashboard visualizes key sales metrics across multiple dimensions—time, geography, and sales personnel—to support data-driven decision-making.


Tools Used

• Database from (Kaggle)

• Data visualization tool ( Microsoft Power BI )

• Data aggregation and cleaning ( Microsoft Excel, Python Programming Language)

Python Power BI Microsoft Excel Kaggle GitHub


Key Features & Insights:

  1. Monthly Sales Trend

• Tracks Sum of Amount from January to August.

• Sales peak in January (900K) and gradually decline toward August (740K).

• Highlights seasonality and potential end-of-year slowdown.

  1. Sales by Country

• Compares sales performance across Australia, UK, India, USA, Canada, and New Zealand.

• Australia leads with (1.14M), followed closely by the UK (1.05M).

• Useful for regional strategy and market prioritization.

  1. Sales by Sales Person • Ranks individual performance, from Chess Bonneil (321K) down to Wilone (139K).

• Enables identification of top performers and those needing support or training.


Business Value

• Provides clear visibility into monthly revenue patterns

• Supports geographic expansion decisions

• Facilitates sales team performance reviews and incentive planning

• Helps identify seasonal trends for inventory and marketing alignment


About

This project presents a comprehensive sales analytics dashboard for a chocolate manufacturing company. The dashboard visualizes key sales metrics across multiple dimensions—time, geography, and sales personnel—to support data-driven decision-making

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