data_products

Creates, updates, deletes, gets or lists a data_products resource.

Overview

Name	data_products
Type	Resource
Id	aws.datazone.data_products

Fields

The following fields are returned by SELECT queries:

get_data_product

Name	Datatype	Description
id	string	The ID of the data product. (pattern: <code>[a-zA-Z0-9_-]{1,36}</code>)
name	string	The name of the data product.
created_at	string (date-time)	The timestamp at which the data product is created.
created_by	string	The user who created the data product.
description	string	The description of the data product.
domain_id	string	The ID of the domain where the data product lives. (pattern: <code>dzd[-][a-zA-Z0-9-]{1,36}</code>)
first_revision_created_at	string (date-time)	The timestamp at which the first revision of the data product is created.
first_revision_created_by	string	The user who created the first revision of the data product.
forms_output	array	The metadata forms of the data product.
glossary_terms	array	The glossary terms of the data product.
items_	array	The data assets of the data product.
owning_project_id	string	The ID of the owning project of the data product. (pattern: <code>[a-zA-Z0-9_-]{1,36}</code>)
revision	string	The revision of the data product.
status	string	The status of the data product. (CREATED, CREATING, CREATE_FAILED)

Methods

The following methods are available for this resource:

Name	Accessible by	Required Params	Optional Params	Description
get_data_product	select	domain_identifier, identifier, region	revision	Gets the data product. Prerequisites: The data product ID must exist. The domain must be valid and accessible. User must have read or discovery permissions for the data product.
create_data_product	insert	domain_identifier, region, name, owningProjectIdentifier		Creates a data product. A data product is a comprehensive package that combines data assets with their associated metadata, documentation, and access controls. It's designed to serve specific business needs or use cases, making it easier for users to find and consume data appropriately. Data products include important information about data quality, freshness, and usage guidelines, effectively bridging the gap between data producers and consumers while ensuring proper governance. Prerequisites: The domain must exist and be accessible. The owning project must be valid and active. The name must be unique within the domain (no existing data product with the same name). User must have create permissions for data products in the project.
delete_data_product	delete	domain_identifier, identifier, region		Deletes a data product in Amazon DataZone. Prerequisites: The data product must exist and not be deleted or archived. The user must have delete permissions for the data product. Domain and project must be active.

Parameters

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

Name	Datatype	Description
domain_identifier	string	The ID of the Amazon DataZone domain in which the data product is deleted.
identifier	string	The identifier of the data product that is deleted.
region	string	AWS region (default: us-east-1)
revision	string	The revision of the data product.

SELECT examples

get_data_product

Gets the data product. Prerequisites: The data product ID must exist. The domain must be valid and accessible. User must have read or discovery permissions for the data product.

SELECT
id,
name,
created_at,
created_by,
description,
domain_id,
first_revision_created_at,
first_revision_created_by,
forms_output,
glossary_terms,
items_,
owning_project_id,
revision,
status
FROM aws.datazone.data_products
WHERE domain_identifier = '{{ domain_identifier }}' -- required
AND identifier = '{{ identifier }}' -- required
AND region = '{{ region }}' -- required
AND revision = '{{ revision }}'
;

INSERT examples

create_data_product

Creates a data product. A data product is a comprehensive package that combines data assets with their associated metadata, documentation, and access controls. It's designed to serve specific business needs or use cases, making it easier for users to find and consume data appropriately. Data products include important information about data quality, freshness, and usage guidelines, effectively bridging the gap between data producers and consumers while ensuring proper governance. Prerequisites: The domain must exist and be accessible. The owning project must be valid and active. The name must be unique within the domain (no existing data product with the same name). User must have create permissions for data products in the project.

INSERT INTO aws.datazone.data_products (
name,
owningProjectIdentifier,
description,
glossaryTerms,
formsInput,
items,
clientToken,
domain_identifier,
region
)
SELECT 
'{{ name }}' /* required */,
'{{ owningProjectIdentifier }}' /* required */,
'{{ description }}',
'{{ glossaryTerms }}',
'{{ formsInput }}',
'{{ items }}',
'{{ clientToken }}',
'{{ domain_identifier }}',
'{{ region }}'
RETURNING
id,
name,
created_at,
created_by,
description,
domain_id,
first_revision_created_at,
first_revision_created_by,
forms_output,
glossary_terms,
items_,
owning_project_id,
revision,
status
;

Manifest

# Description fields are for documentation purposes
- name: data_products
props:
  - name: domain_identifier
    value: "{{ domain_identifier }}"
    description: Required parameter for the data_products resource.
  - name: region
    value: "{{ region }}"
    description: Required parameter for the data_products resource.
  - name: name
    value: "{{ name }}"
  - name: owningProjectIdentifier
    value: "{{ owningProjectIdentifier }}"
  - name: description
    value: "{{ description }}"
  - name: glossaryTerms
    value:
      - "{{ glossaryTerms }}"
  - name: formsInput
    value:
      - formName: "{{ formName }}"
        typeIdentifier: "{{ typeIdentifier }}"
        typeRevision: "{{ typeRevision }}"
        content: "{{ content }}"
  - name: items
    value:
      - itemType: "{{ itemType }}"
        identifier: "{{ identifier }}"
        revision: "{{ revision }}"
        glossaryTerms: "{{ glossaryTerms }}"
  - name: clientToken
    value: "{{ clientToken }}"

DELETE examples

delete_data_product

Deletes a data product in Amazon DataZone. Prerequisites: The data product must exist and not be deleted or archived. The user must have delete permissions for the data product. Domain and project must be active.

DELETE FROM aws.datazone.data_products
WHERE domain_identifier = '{{ domain_identifier }}' --required
AND identifier = '{{ identifier }}' --required
AND region = '{{ region }}' --required
;