The Coffee Shop Analytics project is designed to analyze sales data from a coffee shop, focusing on understanding customer behavior, product performance, and sales trends. The project utilizes transaction records organized into detailed data sheets and summarized with pivot tables, making it a powerful tool for deriving insights and driving business decisions.
The project consists of the following sheets:
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Sheet1 (Raw Data):
Contains detailed transaction records including transaction ID, date, store location, product information, and sales amounts. This sheet serves as the foundational data source for the analysis. -
Pivot (Summary Data):
A pivot table that aggregates data from the raw transactions, summarizing key metrics such as total sales, transaction counts, and product performance across various dimensions like day of the week, product category, and more. -
Dashboard (Visualization):
A reserved sheet for creating visual dashboards. This can be used to build charts, graphs, and other visual tools that present insights derived from the data.
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Data Exploration:
Begin by exploring Sheet1 to gain detailed insights into individual transactions. -
Data Analysis:
Use the Pivot sheet to view summarized data and identify trends across different categories and time periods. -
Visualization:
Create dashboards in the Dashboard sheet by leveraging the summarized data from the Pivot sheet. These visualizations will help in easily interpreting key insights.
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Software:
Microsoft Excel or any compatible spreadsheet software is required to view and manipulate the data. -
Skills:
Basic knowledge of Excel, including pivot tables and chart creation, is recommended to maximize the utility of this project.
This project is a comprehensive tool for analyzing coffee shop sales data, providing both raw and summarized data for in-depth analysis and visualization. It's designed to support data-driven decision-making by revealing patterns and trends that can improve business strategies.
