Locations dataset

Locations dataset containing metadata for stores, distribution centres, and other inventory sites used by the Rebuy & Replenishment capability of the Merchandising solution.

The locations dataset contains metadata for the locations used by the Rebuy & Replenishment capability. Locations typically represent stores, distribution centres, or other sites where inventory is stored, replenished, or planned.

This dataset provides contextual information about where inventory exists and how locations function within the supply chain.

Purpose

The Rebuy & Replenishment capability uses the locations dataset to:

• Identify where inventory is held or replenished
• Distinguish between different types of locations, such as stores and distribution centres
• Support analysis and reporting across the supply network

During analysis, location metadata helps the solution correctly interpret inventory flows and planning behavior across the network.

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 location.	string	Primary key
location_name	Name of the location.	string	Nullable
country	Country where the location is based.	string	Nullable
is_store	Indicates whether the location is a store.	boolean	Non-null
is_dc	Indicates whether the location is a distribution centre.	boolean	Non-null
is_factory	Indicates whether the location is a manufacturing facility.	boolean	Non-null

Usage notes

• Every location referenced in other datasets (for example, Stock, Sales, Purchase orders, or Transfers) must exist in the locations dataset.
• Location identifiers must be consistent across all datasets.
• The is_store, is_dc, and is_factory flags help distinguish how locations are treated in planning and analysis.
• If additional location attributes are required for specific use cases, they can be incorporated during onboarding.