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Supply Chain & Retail Solutions user guide
- Overview
- Platform setup and administration
- Platform setup and administration
- Platform architecture
- Data Bridge onboarding overview
- Connecting a Peak-managed data lake
- Connecting a customer-managed data lake
- 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
- Using Snowflake with Peak
- SQL Explorer overview
- Roles and permissions
- User management
- Inventory management solution
- Commercial pricing solution
- Merchandising solution
Sales dataset containing aggregated daily sales per product and location, an optional demand-history signal for Inventory Management.
The sales dataset contains aggregated daily sales for each product at each location. It is an optional alternative or complement to the Customer orders dataset as a demand-history signal.
Purpose
The inventory management solution uses aggregated sales data to understand historical demand at the product and location level. This dataset can be provided instead of, or in addition to, the Customer orders dataset when order-line level data is not available or when aggregated demand history is preferred.
Required fields
| Field | Description | Type | Use | Notes |
|---|---|---|---|---|
product_id | Unique identifier for the product SKU. | string | Application | N/A |
location_id | Unique identifier for the store or distribution centre. | string | Application | N/A |
day_date | Date corresponding to the reported sales. | date | Application | N/A |
sales_units | Number of units sold for the given product, location, and date. | float | Application | N/A |
sales_value | Revenue value of the units sold. | float | Application | Should correspond to the value of sales_units. |
Usage notes
- This dataset is an optional alternative or complement to the Customer orders dataset.
- A daily record of sales is recommended to support accurate demand analysis.
- Product and location identifiers must align with the corresponding Products and Locations datasets.
- Sales quantities should use the same unit of measure as related datasets.