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Retail Business Operations Data
Retail & Consumer Behavior
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About
Exploring the operations of an online shop, this dataset details orders and products. It is structured into two tables: one focusing on transactional order details and another on product information. This data serves as a valuable resource for understanding retail performance, analysing product trends, and formulating effective business strategies within an e-commerce context.
Columns
The dataset is composed of two primary tables:
Orders Table:
order_id: A unique number that distinguishes each customer order.order_date: The specific date when the order was placed.product_id: The identification number of the product that was ordered.quantity: The number of units of each product included in the order.total_price: The total amount the customer is required to pay for the order.
Products Table:
product_id: A unique number that distinguishes each individual product.product_name: The name assigned to each product.category: The specific category to which the product belongs, such as books or electronics.price: The selling price of each product.
Distribution
The data is typically available in a CSV file format, with sample files updated separately to the platform. The
orders.csv file, for instance, has a size of 3.08 kB. The orders table contains 100 valid records for each of its columns including order_id, order_date, product_id, quantity, and total_price. Specific numbers for rows or records in the products table are not explicitly detailed.Usage
This dataset is ideal for various analytical applications, including:
- Sales forecasting: Predicting future sales trends and patterns.
- Inventory management: Optimising stock levels based on product demand.
- Customer segmentation: Identifying different customer groups based on purchasing behaviour.
- Product trend analysis: Understanding popular products and categories over time.
- Pricing strategies: Developing and evaluating pricing models.
- Time series analysis: Analysing temporal patterns in order data.
Coverage
The dataset primarily covers order and product information for a period ranging from 11 January 2023 to 22 December 2023. There is no specific geographic or demographic scope provided within the data.
License
CC0: Public Domain
Who Can Use It
This data is particularly beneficial for:
- Data Analysts: To derive insights into sales performance and customer behaviour.
- Business Intelligence Professionals: For creating reports and dashboards to monitor key retail metrics.
- Data Scientists: To build predictive models for sales, inventory, or customer churn.
- E-commerce Managers: To make informed decisions on product offerings, promotions, and operational efficiency.
- Students and Researchers: For academic projects and studies related to retail, e-commerce, and business analytics.
Dataset Name Suggestions
- Online Retail Transactions 2023
- E-commerce Order and Product Data
- Digital Shop Sales Analytics
- Retail Business Operations Data
- Product Sales & Order History
Attributes
Original Data Source Link: Retail Business Operations Data
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