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Synthetic Sales Transactions
Synthetic Data Generation
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About
This dataset is a collection of synthetic sales data, specifically created for practice, educational, and testing purposes. It is not based on actual business operations or real-time sales. The dataset simulates sales transactions across various products, regions, and customers, with each row detailing an individual sale event.
Columns
- Product_ID: A unique identifier for each product sold, randomly generated for practice purposes.
- Sale_Date: The date the sale occurred, randomly selected from the year 2023.
- Sales_Rep: The sales representative responsible for the transaction. The dataset includes five random representatives: Alice, Bob, Charlie, David, and Eve.
- Region: The geographical region where the sale took place, with possible regions being North, South, East, and West.
- Sales_Amount: The total sales amount for the transaction, including any discounts, with values ranging from 100 to 10,000 in currency units.
- Quantity_Sold: The number of units sold in that transaction, randomly generated between 1 and 50.
- Product_Category: The category of the product sold, including Electronics, Furniture, Clothing, and Food.
- Unit_Cost: The cost per unit of the product sold, randomly generated between 50 and 5000 currency units.
- Unit_Price: The selling price per unit of the product, calculated to be higher than the unit cost.
- Customer_Type: Indicates whether the customer is a New or Returning customer.
- Discount: The discount applied to the sale, randomly chosen between 0% and 30%.
- Payment_Method: The method of payment used by the customer, such as Credit Card, Cash, or Bank Transfer.
- Sales_Channel: The channel through which the sale occurred, either Online or Retail.
- Region_and_Sales_Rep: A combined column pairing the region and sales representative for ease of tracking.
Distribution
The dataset is typically provided in CSV format, with a file size of approximately 105.08 KB [1]. It contains 14 columns [1] and approximately 1000 individual sale records or rows [2-10]. Each row represents a single sale event [11].
Usage
This dataset is ideal for various practice, learning, and testing scenarios [11, 12]. It can be effectively used for:
- Data Analytics [1]
- Data Visualization [1]
- Exploratory Data Analysis [1]
- Developing and testing machine learning models, particularly those involving categorical data or techniques like Random Forest [1].
Coverage
- Geographic Scope: Sales data covers four distinct regions: North, South, East, and West [13].
- Time Range: All sale dates are randomly selected from the year 2023 [2, 13].
- Demographic Scope: Customer interactions are categorised by 'New' or 'Returning' customer types [14], and transactions are attributed to five different sales representatives: Alice, Bob, Charlie, David, and Eve [13].
License
CC0: Public Domain
Who Can Use It
This dataset is designed for individuals and organisations engaged in data education, analysis, and software development. Examples of intended users and their use cases include:
- Students and Learners: For understanding data structures, practicing data cleaning, and developing fundamental analytical skills [11, 12].
- Data Analysts and Scientists: For creating dashboards, performing statistical analysis, and training predictive models [1].
- Developers: For testing data processing pipelines or integrating simulated sales data into applications.
Dataset Name Suggestions
- Synthetic Sales Transactions
- Practice Sales Data
- Simulated Retail Sales
- Fictitious Sales Records
- Educational Sales Dataset
Attributes
Original Data Source: Synthetic Sales Transactions
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