Sales dataset

Sales dataset for the Markdown & Promotions module, containing historical sales and return transactions per product and location.

The Sales dataset contains historical sales and return transactions for each product at each location. It is the primary demand signal used by the Markdown & Promotions module to understand product performance.

Purpose

The Markdown & Promotions module uses the Sales dataset to:

• Provide historical demand and sales performance by product and location
• Capture returns alongside gross sales for net performance analysis
• Support evaluation of markdown and promotion impact over time

Required fields

About the Constraint column: every field listed must be provided in your data. Non-null means its value cannot be null; Nullable means the value may be sent as null (or left blank in your source). Primary key, Unique, and Foreign key describe the field's role in the data model; a Primary key is always non-null.

Field	Description	Type	Constraint
location_id	Unique identifier for the store or location.	string	Primary key Foreign key to location
product_id	Unique identifier for the product SKU.	string	Primary key Foreign key to product
sold_at	Timestamp when the sale occurred.	timestamp	Primary key
created_at	Timestamp when the record was created.	timestamp	Nullable
customer_id	Identifier for the customer associated with the transaction.	string	Nullable
demand_units	Number of units demanded or ordered.	float	Nullable
demand_value	Total value of the demanded units.	float	Nullable
return_units	Number of units returned.	integer	Non-null
return_value	Total value of the returned units.	float	Non-null
returned_at	Timestamp when items were returned.	timestamp	Nullable
sale_id	Source-system identifier for the sale.	string	Nullable
sales_units	Net units sold, after returns.	integer	Non-null
sales_value	Net sales value, after returns.	float	Non-null
shipped_at	Timestamp when items were shipped.	timestamp	Nullable
updated_at	Timestamp when the record was last updated.	timestamp	Nullable

Usage notes

• Product and location identifiers must align with the Products and Locations datasets.
• Units should use the same unit of measure as related datasets (for example, Stock).
• A complete history improves the accuracy of demand analysis.

Why this dataset matters

Sales history is the core demand signal. Without it, the solution cannot assess product performance or the impact of markdowns and promotions.