- 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
Required datasets for Rebuy & Replenishment in the UiPath Merchandising solution, including product, location, stock, sales, and hierarchy data.
This page lists the data Rebuy & Replenishment (part of the Merchandising solution) needs and what each dataset is used for. To connect your systems and load this data into the platform, see Data ingestion.
The capability works from data you already have — sales, products, inventory positions, and planning parameters. During onboarding these are mapped and ingested from your existing systems; you don't create or edit them in the solution. The capability then uses them to generate inventory insights and replenishment recommendations for you to review and act on.
Rebuy & Replenishment is designed for retail selling to end consumers, so its data differs from standard inventory management:
- Demand history comes from aggregated sales rather than order-line customer orders.
- A products parent child mapping dataset captures product hierarchies and substitutions (for example, size or colour variants).
- Manufacturing orders and forecast datasets are not required.
Required datasets
The following datasets are required to run Rebuy & Replenishment. Datasets marked Optional add extra signal where you have the data.
| Business data category | Description | Dataset(s) in this guide |
|---|---|---|
| Product data | Defines the items that are planned and managed by the solution. | Products dataset |
| Location data | Defines the locations where inventory is held, replenished, or planned. | Locations dataset |
| Inventory position data | Provides current on-hand inventory quantities by product and location. | Stock dataset |
| Demand history | Provides historical sales data used to understand demand patterns over time. | Sales dataset |
| Replenishment parameters | Defines planning inputs such as lead times, reorder policies, or replenishment constraints. | Order parameters dataset |
| Service-level targets or business objectives | Defines target service levels or objectives used to evaluate trade-offs between availability and inventory cost. | Order parameters dataset (service_level field) |
| Inbound supply data | Represents incoming stock from suppliers or internal transfers used to project future inventory availability. | Purchase orders dataset Transfers dataset |
| Financial context data | Provides cost and price information used to assess the financial impact of inventory decisions. | Pricing dataset |
| Supplier metadata | Defines suppliers associated with replenishment and sourcing activities. | Suppliers dataset |
| Product hierarchy data | Defines parent-child relationships between products for substitution and hierarchy modelling. | Products parent child mapping dataset |
| Additional product attributes | Optional. Tenant-specific product attributes in key-value format. | Product extra dataset |
| Product lifecycle | Optional. Active date ranges for products at locations, including discontinuation dates. | SKU calendar dataset |