Region dataset

Region dataset containing geographic region definitions used by the Commercial Pricing solution for pricing differentiation and analysis.

The Region dataset contains geographical region definitions used by the commercial pricing solution. It enables pricing differentiation and analysis across defined geographic segments.

This dataset is required for application deployment and pricing insights analysis.

→ For the canonical technical schema (data types, validation rules, request/response examples), see Region in the API Guide.

Purpose

The solution uses the Region dataset to:

• Segment pricing strategies by geography
• Analyze pricing behavior across regions
• Support regional differentiation in pricing models
• Enable region-level reporting and insights

This dataset allows pricing recommendations to account for geographic variation in demand, cost, and competitive conditions.

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
region_id	Unique identifier for the region.	string	Primary key
region_name	Name of the region.	string	Non-null
updated_at	Timestamp when the record was last updated.	timestamp_tz	Primary key

Custom fields

The fields listed previously are the standard schema for this dataset. A field that your business requires but the standard schema does not include can be added as a custom attribute after the schema is rolled out. Custom attributes are additive, so they extend the dataset without affecting existing fields, and they are validated in the same way as standard fields.

The following request adds a REGION_MANAGER column to this dataset:

curl -X POST \
  'https://ingestion.peak.ai/api/v2/schema/QP_REGION_OOTB/add-attribute' \
  -H 'Authorization: YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "solutionName": "QP_OOTB",
    "columnName": "REGION_MANAGER",
    "dataType": "string",
    "validations": [
      { "type": "optional" }
    ]
  }'

The table name in the request URL is this dataset's fully qualified warehouse name, which includes the prefix and suffix configured when your solution was rolled out — QP_REGION_OOTB in this example. Retrieve the name for your own solution with Describe a solution's schema.

On standard tables the API prefixes the new column name in the warehouse with C_ (Snowflake) or c_ (Redshift), so REGION_MANAGER becomes C_REGION_MANAGER and warehouse queries must use the prefixed name.

→ For the full parameter reference, supported data types, and validation rules, see Customizations in the API Guide.

Usage notes

• Regions should reflect the geographic segmentation used in pricing decisions.
• Region identifiers must align with references in related datasets (for example, Quote Line or Sales, if region-based differentiation is applied).
• Regional definitions should remain consistent over time to preserve analytical continuity.
• Historical stability of region definitions improves pricing model reliability.

Why this dataset matters

The Region dataset enables the solution to evaluate pricing strategies across geographic segments. Without it, pricing analysis may lack necessary geographic context and segmentation accuracy.