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- Overview
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- Platform setup and administration
- Platform architecture
- Data Bridge onboarding overview
- Connecting a Peak-managed data lake
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- Creating an AWS IAM role for Data Bridge
- Connecting a Snowflake data warehouse
- Connecting a Redshift data warehouse (public connectivity)
- Connecting a Redshift data warehouse (private connectivity)
- Reauthorizing a Snowflake OAuth connection
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- SQL Explorer overview
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- Inventory management solution
- Commercial pricing solution
- Merchandising solution
Supply Chain & Retail Solutions user guide
Last updated Apr 16, 2026
Pricing dataset
The pricing dataset contains historical and future cost and retail price information for products over time. It represents how product prices change and is used by the inventory management solution to evaluate the financial impact of inventory decisions.
This dataset can include both historical price changes and planned future prices.
Purpose
The inventory management solution uses the pricing dataset to:
- Evaluate inventory value and exposure in financial terms
- Assess the revenue impact of stock availability or shortages
- Support inventory KPIs that depend on product price, such as lost sales value or capital tied up in overstock
During presales, pricing data is also used to estimate the potential financial impact of inventory optimization.
Required fields
| Field | Description | Type | Use | Notes |
|---|---|---|---|---|
product_id | Unique identifier for the product SKU. | string | Application / Presales | N/A |
location_id | Identifier for the store or distribution centre. | string | Application / Presales | Can be NULL or blank if pricing does not vary by location. |
unit_cost_price | Cost of a single unit of stock to the business during the validity period. | float | Application / Presales | Units must match those used in related datasets (for example, Customer orders and Stock). |
unit_list_price | Retail price of a single unit during the validity period. | float | Application / Presales | N/A |
valid_from | Date and time when the price becomes valid. | datetime | Application / Presales | Can be NULL to indicate validity from any date before valid_to. |
valid_to | Date and time when the price is no longer valid. | datetime | Application / Presales | Can be NULL to indicate validity after valid_from. |
created_at | Date and time (UTC) when the record was created. | datetime | Application | Optional. |
Usage notes
- If both
valid_fromandvalid_toare NULL, the price is assumed to be valid for all dates. - Historical pricing data improves the accuracy of financial impact analysis.
- Pricing units must be consistent with units used in demand and stock datasets.
- When pricing varies by location,
location_idshould be populated accordingly.