Brewing Insights from Coffee Sales: A Dashboard Project

This project proves how tools like Excel when used with intention can unlock powerful insights. And yes, a lot of coffee went into making this coffee dashboard.
Coffee Dashboard
Data Analysis of Coffee Sales Data

Why I Built This
I wanted to turn raw business data into something meaningful. So, I picked a dataset from a coffee company and built a dashboard that answers real questions:
Which countries buy the most?
Who are our top customers?
What’s the best-selling roast?
It was my way of practicing data cleaning, storytelling, and dashboarding all in one project.

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The Data at a Glance
The Excel workbook had several sheets including Orders (every purchase made), Customers (names, emails, locations, loyalty info), Products (prices, roast types, coffee categories), Sales by Country and Top Customers, and a summary sheet for Total Sales. Each sheet held a different puzzle piece of the business story.

Cleaning the Mess
Like most real-world data, this one wasn’t clean. There were missing emails (over 200 rows), coded values like “Ara” for Arabica and “M” for Medium roast, and unparsed date fields. I filled or excluded missing fields where needed, mapped abbreviations to their full names, broke down order dates into year and month for trend analysis, and double-checked that all sales numbers aligned with quantity and price.

Insights I Uncovered
USA topped the charts in total sales, followed by Ireland and the UK. Arabica and Robusta were the most popular coffee types, while Excelsa had fewer buyers but higher spend per order. Medium roast was consistently the favorite across countries. Sales peaked every year in the last quarter likely due to holiday gifting or increased consumption. I also found that customers with loyalty cards tended to order more frequently and spend more per purchase.

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Dashboard Features
I built the dashboard entirely in Excel using Pivot Tables, Power Query, and slicers. It features dynamic filters by country, coffee type, and year, time-based trend lines, top 10 customers by revenue, and a region wise sales map. Every visual is tied to a business question who, what, where, and when.

What I Learned
This project wasn’t just about visuals it trained me to think like a business analyst. I learned to clean before I visualize, to validate assumptions with data, and to build dashboards that offer decision-ready insights.


What started as a few scattered spreadsheets became a complete business story. This project proves how tools like Excel, when used with intention can unlock powerful insights. And yes, a lot of coffee went into making this coffee dashboard.

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