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Europe Sales Records
Retail & Consumer Behavior
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About
This dataset includes sales transaction records across various European countries, covering multiple product categories and sales details. It is designed to analyze business performance and profitability based on diverse features such as region, product type, sales channel, and financial metrics. The dataset provides a realistic challenge for creating data-driven insights in business analytics and financial performance evaluation.
Dataset Features:
- Region: The geographic region of the transaction (e.g., Europe).
- Country: Specific country where the transaction occurred.
- Item Type: The category of the item sold (e.g., Meat, Fruits, Beverages).
- Sales Channel: Whether the transaction occurred Offline or Online.
- Order Priority: Priority level assigned to the order (e.g., M for Medium, H for High, L for Low, and C for Common).
- Order Date: The date the order was placed.
- Order ID: A unique identifier for each order.
- Ship Date: The date the order was shipped.
- Units Sold: The number of units sold in the transaction.
- Unit Price: The price per unit of the product.
- Unit Cost: The cost incurred per unit of the product.
- Total Revenue: Total revenue generated from the transaction.
- Total Cost: Total cost associated with the transaction.
- Total Profit: Profit generated from the transaction.
Usage:
The dataset is ideal for training and testing business analytics models and financial decision-making tools. Potential applications include:
- Analyzing sales trends and profitability.
- Evaluating the impact of regional and product-specific performance.
- Benchmarking business strategies through data visualization and statistical analysis.
- Exploring cost-revenue relationships for financial forecasting.
Coverage:
The dataset spans multiple countries in Europe and encompasses key attributes of sales transactions, supporting various business analytics and modeling techniques.
License:
Proprietary License:
This dataset is provided for non-commercial, educational, and research purposes only; redistribution or commercial use is strictly prohibited without prior consent.
Who Can Use It:
This dataset is intended for business analysts, data scientists, machine learning practitioners, researchers, and students interested in exploring business analytics and financial modeling.
How to Use It:
- Develop models for sales prediction or profitability analysis.
- Conduct feature importance analysis to identify key drivers of profit.
- Perform exploratory data analysis to uncover patterns in sales and cost metrics.
- Benchmark machine learning algorithms in the domain of sales and financial analytics.
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