Products dataset

Products dataset for the Markdown & Promotions module, containing the product reference metadata joined to sales, stock, pricing, and tax datasets.

The Products dataset contains metadata for the products managed by the Markdown & Promotions module. It defines the items included in analysis and provides the descriptive and categorical information used across markdown and promotion decisions.

This dataset acts as a reference dataset and is joined to other datasets, such as Sales, Stock, and Product pricing daily, using the product_id.

Purpose

The Markdown & Promotions module uses the Products dataset to:

• Identify the products included in markdown and promotion analysis
• Enable analysis at both individual product and category levels
• Ensure consistent product identifiers across all related datasets

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
product_id	Unique identifier for the product SKU.	string	Primary key
created_at	Timestamp when the record was created.	timestamp	Nullable
description	Description of the product.	string	Nullable
lowest_product_category_id	Reference to the most specific (leaf) category the product belongs to.	string	Foreign key to product_category Non-null
name	Name of the product.	string	Non-null
updated_at	Timestamp when the record was last updated.	timestamp	Nullable

Usage notes

• Every product referenced in other datasets (for example, Sales, Stock, or Product pricing daily) must exist in the Products dataset.
• The product_id must be consistent across all datasets.
• Category information supports higher-level analysis and reporting.

Why this dataset matters

The Products dataset defines the scope of the Markdown & Promotions module. Without a consistent product reference, the solution cannot reliably join sales, stock, and pricing data or generate meaningful recommendations.