Dataset Templates

Data Products package your extraction and resolution outputs into reusable, shareable artifacts. Dataset Templates define the shape; Assemblies combine sources into a single structured dataset.

A dataset template defines a reusable output specification: which schema to use, which document types to include, column mappings, and default transforms. Templates ensure consistent data product generation across teams and time periods.

Navigate to Data Products → Dataset Templates to manage templates. Each template is linked to a user schema and can be versioned independently. When creating a new job, select a template instead of configuring the output from scratch.

Templates support column mappings that rename, reorder, or exclude fields from the output. Default transforms — such as date formatting, currency normalization, or unit conversion — are applied automatically during assembly. This means every data product built from the same template produces structurally identical output regardless of who runs it or when.

For best results, create one template per downstream consumer. If your finance team and operations team need different column subsets from the same schema, define two templates rather than manually reconfiguring each export. Most teams version their templates alongside schema changes to maintain backward compatibility with existing integrations.

To create a dataset template, navigate to Data Products → Dataset Templates and click New Template. Select the user schema that defines the field set, then configure column mappings to rename, reorder, or exclude fields from the output. Add default transforms — such as date formatting to ISO 8601, currency normalization to a base currency, or unit conversion — that run automatically during assembly. Save the template and it becomes available to any team member when creating a new job or assembly.

• Linked to a user schema — fields are inherited automatically as the schema evolves
• Column mappings: rename, reorder, or exclude fields from the final output
• Default transforms: date formatting, currency normalization, unit conversion
• Independent versioning: evolve the template without affecting existing data products
• Workspace-scoped: any team member can create, edit, or use any template
• One template per downstream consumer is the recommended pattern

curl -s https://api.talonic.com/v1/data-products \
  -H "Authorization: Bearer $TALONIC_API_KEY"

# Response:
# {
#   "data_products": [
#     {
#       "id": "dp_001",
#       "name": "Q1 2025 Invoice Extract",
#       "schema_name": "Invoice Extraction",
#       "document_count": 245,
#       "status": "completed",
#       "created_at": "2025-04-01T08:00:00Z"
#     }
#   ],
#   "total": 8
# }

Dataset templates are the bridge between schemas and production-ready data products. While a schema defines what fields to extract, a template defines how those fields appear in the final output — column order, renamed headers, excluded fields, and default transforms. This separation means you can create multiple templates from the same schema for different downstream consumers. For example, your finance team might need all 20 invoice fields in EUR format, while your operations team needs only 8 fields in USD format. Two templates, one schema, consistent extraction.