About this file The Kaggle Global Superstore dataset is a comprehensive dataset containing information about sales and orders in a global superstore. It is a valuable resource for data analysis and visualization tasks. This dataset has been processed and transformed from its original format (txt) to CSV using the R programming language. The original dataset is available here, and the transformed CSV file used in this analysis can be found here.

Here is a description of the columns in the dataset:

category: The category of products sold in the superstore.

city: The city where the order was placed.

country: The country in which the superstore is located.

customer_id: A unique identifier for each customer.

customer_name: The name of the customer who placed the order.

discount: The discount applied to the order.

market: The market or region where the superstore operates.

ji_lu_shu: An unknown or unspecified column.

order_date: The date when the order was placed.

order_id: A unique identifier for each order.

order_priority: The priority level of the order.

product_id: A unique identifier for each product.

product_name: The name of the product.

profit: The profit generated from the order.

quantity: The quantity of products ordered.

region: The region where the order was placed.

row_id: A unique identifier for each row in the dataset.

sales: The total sales amount for the order.

segment: The customer segment (e.g., consumer, corporate, or home office).

ship_date: The date when the order was shipped.

ship_mode: The shipping mode used for the order.

shipping_cost: The cost of shipping for the order.

state: The state or region within the country.

sub_category: The sub-category of products within the main category.

year: The year in which the order was placed.

market2: Another column related to market information.

weeknum: The week number when the order was placed.

This dataset can be used for various data analysis tasks, including understanding sales patterns, customer behavior, and profitability in the context of a global superstore.

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Global Superstore Data Overview

The provided dataset consists of three related files from a global superstore:

Orders: Contains detailed records of customer orders.

Returns: Lists orders that have been returned.

People: Maps sales personnel to specific sales regions.

Together, these files can be used to analyze sales performance, profitability, shipping efficiency, and return rates across different products, customers, and geographical locations.

Analyze 5,000 retail orders with $1.3M in sales data. The definitive Tableau practice dataset for business intelligence, featuring customer segments, product categories, regional performance, and profit margin analysis across 3 years of US retail transactions.

Context

With growing demands and cut-throat competitions in the market, a Superstore Giant is seeking your knowledge in understanding what works best for them. They would like to understand which products, regions, categories and customer segments they should target or avoid.

Retail dataset of a global superstore for 4 years.

You can even take this a step further and try and build a Regression model to predict Sales or Profit.

Go crazy with the dataset, but also make sure to provide some business insights to improve.

Metadata

Order ID => Unique Order ID for each Customer.

Order Date => Order Date of the product.

Ship Date => Shipping Date of the Product.

Ship Mode=> Shipping Mode specified by the Customer.

Customer Name => Name of the Customer.

Segment => The segment where the Customer belongs.

State => State of residence of the Customer.

Country => Country of residence of the Customer.

Market => The market place of the product.

Region => Region where the Customer belong.

Product ID => Unique ID of the Product.

Category => Category of the product ordered.

Sub-Category => Sub-Category of the product ordered.

Product Name => Name of the Product

Unit Price => The price for one unit.

Quantity => Quantity of the Product.

Discount => Discount provided.

Shipping Cost => The cost for shipping

Order Priority => Items shipped via priority are shipped by air which results in faster delivery times.

Sales => Sales of the Product.

Expenses => The expense is the cost of operations that a company incurs to generate revenue.

Revenue => The Revenue refers to the total earnings.

Year => Year of the Sales.

Acknowledgements

I do not own this data. I merely found it from the Tableau website and add some row. All credits to the original authors/creators. For educational purposes only.

The Superstore Retail Dataset is the most popular starter dataset in analytics: four years of retail orders across regions, customer segments and product categories, with sales, quantity, discount and profit on every line. It’s the fastest path to your first end-to-end Power BI or Excel dashboard and a great SQL playground for joins, aggregations and window functions.

The PGA Tour Superstore dataset provides structured data from PGA Tour Superstore's platform, covering url, item_id, variant_id, title, description, product_category, category_tree, brand. Use cases include competitive analysis, market research, and data enrichment.

Analyze sales trends, customer segments, and profit margins across products and regions with this dataset. Ideal for AI/ML models in business analytics, forecasting, and customer behavior studies.

Dataset

This dataset was created by Patricia Hunt

Contents

Procurement intelligence dataset for AED SUPERSTORE including contracts, agency relationships, and vendor activity.

Yonghui Superstore reported CNY14.02B in Debt for its fiscal quarter ending in March of 2026.Data for Yonghui Superstore | 601933 - Debt including historical, tables and charts were last updated by Trading Economics this last October in 2026.

Yonghui Superstore reported CNY-78.54M in EBIT for its fiscal quarter ending in June of 2026.Data for Yonghui Superstore | 601933 - Ebit including historical, tables and charts were last updated by Trading Economics this last October in 2026.

View Gg Superstore import export trade data, including shipment records, HS codes, top buyers, suppliers, trade values, and global market insights.

K&G Fashion Superstore location dataset: 6 locations in Illinois. Part of CREHQ's multi-unit intelligence platform covering retail, restaurant, financial services, and healthcare brands. Licensed access via enterprise API or dataset purchase. Training on CREHQ data is not permitted.

K&G Fashion Superstore location dataset — 1 locations in Missouri. Part of CREHQ's multi-unit intelligence platform covering retail, restaurant, financial services, and healthcare brands. Licensed access via enterprise API or dataset purchase. Training on CREHQ data is not permitted.

Dataset

This dataset was created by Shubham Jagtap

Contents

This is the revised dataset based on the Excel file from tableau.com, which includes the sales data for a superstore from January 2014 to December 2017 (4 years' data).

This dataset can be used to learn time series analysis, cohort analysis, etc.

Yonghui Superstore reported 0.58 in Dividend Yield for its fiscal quarter ending in March of 2023.Data for Yonghui Superstore | 601933 - Dividend Yield including historical, tables and charts were last updated by Trading Economics this last October in 2026.

Superstore Private Limited recorded an import turnover of USD 1,052,052.72 million and an export turnover of USD 0 between September 2024 and August 2025. Explore detailed trade value insights, supply chain analytics, HS code-wise data, shipment history, partner countries, customs trade values, top import and export commodities with pricing, buyers, suppliers, ports, and key competitors in Sri Lanka.

K&G Fashion Superstore location dataset — 3 locations in Massachusetts. Part of CREHQ's multi-unit intelligence platform covering retail, restaurant, financial services, and healthcare brands. Licensed access via enterprise API or dataset purchase. Training on CREHQ data is not permitted.

Yonghui Superstore reported CNY479.27M in EBITDA for its fiscal quarter ending in March of 2026.Data for Yonghui Superstore | 601933 - Ebitda including historical, tables and charts were last updated by Trading Economics this last October in 2026.