Collibra Operating Model for Latttice
The Latttice Collibra Operating Model defines how Latttice data product entities are represented within the Collibra Data Intelligence Platform.
This model enables Latttice to integrate directly with Collibra’s governance framework by mapping Latttice entities such as Data Products, Ports, Fields, AI Models, and Policies to Collibra asset types, attributes, and relationships.
The purpose of this operating model is to ensure that data products created in Latttice are fully governed, discoverable, and traceable within Collibra.
Overview
The operating model defines four key elements:
Collibra community and domain configuration
Asset type mappings
Attribute mappings
Relationship mappings
These configurations allow Latttice to synchronize metadata and governance structures with Collibra automatically.
Community and Domain Configuration
Latttice publishes metadata into a predefined Collibra community and domain.
This ensures that all Latttice data products and related assets are organized consistently within the Collibra catalog.
Community. The Collibra community where Latttice metadata is stored. eg. "Default Community".
Domain. The domain used to organize Latttice assets. eg. "Default Domain"
Domain Type. Latttice typically uses the Physical Data Dictionary domain type so that data product components such as tables and columns align with Collibra’s physical data asset model. (The Domain Type ID also needs to be included).
Latttice Asset Types
Latttice entities are mapped to specific Collibra asset types. These asset types allow data product structures to be represented within Collibra. These include:
Data Product. Represents a business-level data product definition. A data product contains input ports, output ports, policies, and metadata describing the business purpose of the product.
Data Product Ports. Ports define the interfaces through which data enters or exits a data product.
Data Product Input Port. Represents the source interface through which a data product consumes data. Input ports define the structure of incoming data and reference the underlying datasets or services providing the data. Typically this has a hierarchy of Data Asset > Data Product Port.
Data Product Output Port. Represents the interface through which a data product publishes data. Output ports expose the fields available for consumption by applications, analytics platforms, or AI systems. Typically this has a hierarchy of Data Asset > Data Product Port.
Latttice Field Structures. Latttice defines additional field-level asset types to represent the structure of data products.
Latttice Field Column. Represents a standard output column exposed by a data product. Typically this has a hierarchy of hierarchy of Data Asset > Data Product Port > Data Product Output Port
Latttice Derived Field. Represents a calculated or derived field created using Latttice transformations.
Latttice Output AI Field Column. Represents a column produced by an AI model or AI enrichment process.
Latttice Input AI Field Column. Represents fields used as inputs to an AI model within a data product.
Latttice AI Model. Represents an AI model used within a data product pipeline. AI models can consume input ports and produce AI-generated output fields. Typically this has a hierarchy of hierarchy of Data Asset > Data Structure > Table.
Governance Policy Assets. Latttice introduces governance policies that control how data products can be accessed and used.
Latttice Control Policy. Represents a governance policy applied to a data product or field.
Policies can include:
Attribute Based Controls (ABAC)
Fine Grained Access Controls (FGA)
Purpose Based Controls (PBAC)
Latttice Attributes. Latttice uses Collibra attributes to store metadata describing data products and policies.
Data Product Attributes
Trust Score. Represents the confidence level in the quality and reliability of the data product.
Business Case. Describes the business purpose and value delivered by the data product. This attribute helps business users understand why the data product exists and how it supports decision making.
Policy Attributes. Latttice policies use additional attributes to describe policy behavior.
Control Policy ID. Unique identifier for a policy.
Control Policy Name. Human readable name of the policy.
Control Policy Type. Defines the policy category such as ABAC, FGA, or PBAC
Policy Enforcement Type. Defines how the policy is applied.
Policy Expression. Defines the rule logic used to enforce the policy.
Relationship Model. Latttice relies on a structured set of relationships between assets to represent data product architecture inside Collibra.
Data Product Port Relationships
Port Consumes Data Through Data Product. This relationship defines which data product a port interacts with.
Port Implements Data Product Port Asset. This relationship connects logical ports with physical asset representations.
Input Port Contains AI Field. Defines the fields used as inputs to AI models.
Output Port Contains Field. Defines fields produced by AI or data transformations.
Column Belongs to Table. Standard physical data dictionary relationship.
Policy Relationships.
Policy Governs Field. This relationship defines which fields are affected by governance policies.
Policy Governs Data Product. Allows governance rules to apply at the data product level.
Policy Constrains Output Port. Defines policy restrictions on the exposed output interface of a data product.
How the Operating Model Works
When a data product is created in Latttice:
The Data Product asset is created in Collibra.
Input and output ports are generated.
Fields and derived fields are registered.
AI models and AI fields are linked to the product.
Governance policies are applied.
Relationships are created to form the data product graph.
This model enables Collibra to visualize:
data product architecture
governance policies
field lineage
AI model dependencies
consumption interfaces
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