Project data model

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What is a project data model?

The Project Data Model (PDM) lets you define reusable data types at the project level. These data types propagate to the process data models, ensuring data consistency across your FlowX.AI applications, including in Reusable Functions, Persistence Layer schemas, and other components. With PDM, you create a centralized data structure that serves as the foundation for all processes within your project. This ensures that core data types like Customer, Product, or Document maintain consistent definitions throughout your application.

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Key concepts

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Benefits of project data model

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How to use the project data model

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Access the project data model

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Define a project data model

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Manage data types

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Add a data type

1. Click + in the Data Types panel.
2. Enter the name and properties of the data type.
3. Use the inline Add attribute button on the data type to add attributes.
4. Save changes.

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Edit a data type

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Attribute path

Each attribute displays a path button next to its name. Click it to view the full key path and copy it to your clipboard. This is useful when referencing keys in business rules, UI component bindings, or integration mappings.

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Remove a data type

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Working with referenced data types

When a data type from the Project Data Model is used in a Process Data Model:

1. The Process Data Model will display the referenced data type.
2. The referenced data type cannot be modified at the process level.
3. Changes to the data type in the Project Data Model will propagate to all referencing processes.

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Common scenarios

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Use the Project Data Model in processes

1. Navigate to a process within your project.
2. Open the Process Data Model.
3. Project data types are available for selection.
4. Select the desired project data type to use in your process.
5. The data type is added to your Process Data Model, maintaining reference to the Project Data Model.

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Work with libraries

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Integrate Library Data Models

1. Navigate to your project dependencies.
2. Add a library as a dependency. The library must have a build created.

3. Library data types become available in your Project Data Model.

4. You can now use the library data types in your data model.

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Handle duplicate types from libraries

When multiple libraries contain data types with the same name:

1. Both types will be visible in the Project Data Model with visual indicators.
2. Namespacing functionality will prevent technical issues.

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Configure reporting and sensitive data settings

You can configure reporting and sensitive data settings directly from the attribute settings side panel:

1. Go to the Project Data Model.
2. Select an attribute to open the settings side panel.
3. Toggle Sensitive data or Use in Reporting as needed.

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Project Data Model after version commitment

After committing a project version:

1. The Project Data Model becomes read-only.
2. You can still view the diagram and monitor usage.
3. This read-only configuration is available for any configuration on committed versions and applies also to resource data models.

3. To make changes to the data model, you will require a new project version.

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Search and filter

The Project Data Model interface provides tools to help you find and work with your data types:

1. Navigate to the Project Data Model.
2. By default, only project-level types are displayed.
3. Use filters to view library types as well.
4. Use the search function to find specific types by name.

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Update library dependencies

When updating library dependencies:

1. Navigate to the dependencies section.
2. Select the new library version.
3. The system will inform you of any breaking changes to data types.
4. You can decide whether to proceed with the update.
5. If you proceed, changes will propagate to processes according to compatibility rules.

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Real-world example: Insurance claims processing

Core data types in PDM

The insurance company created these data types in their Project Data Model:

1. Customer
   • customerId: string
   • firstName: string
   • lastName: string
   • dateOfBirth: date
   • contactInformation: ContactInfo (reference)
   • policyNumbers: array of string
   • customerSince: date
   • riskProfile: RiskProfile (reference)
   • Settings: Sensitive data = True, Used in reporting = True
2. ContactInfo
   • email: string
   • phone: string
   • address: Address (reference)
   • Settings: Sensitive data = True, Used in reporting = False
3. Claim
   • claimId: string
   • policyNumber: string (reference to Policy)
   • claimType: enum [“Auto”, “Property”, “Medical”, “Liability”]
   • incidentDate: date
   • reportedDate: date
   • status: enum [“New”, “Under Review”, “Pending Documents”, “Approved”, “Denied”, “Closed”]
   • estimatedAmount: number
   • approvedAmount: number
   • documents: array of Document (reference)
   • Settings: Sensitive data = False, Used in reporting = True
4. Document
   • documentId: string
   • documentType: string
   • fileName: string
   • fileUrl: string
   • uploadDate: date
   • Settings: Sensitive data = False, Used in reporting = False

Process-specific data models

The company created multiple processes using the PDM:

• Auto Claim Processing
• Policy Renewal Process

Root: ClaimProcess

Data Structure:

• ClaimProcess (Process-specific type)
  • claim: Claim (reference from PDM)
  • assignedAdjuster: string
  • vehicleInfo: AutoClaimDetails (reference)
  • processingStage: enum [“Initial Review”, “Damage Assessment”, “Liability Determination”, “Settlement Negotiation”, “Payment Processing”]
• AutoClaimDetails (Process-specific type)
  • vehicleMake: string
  • vehicleModel: string
  • vehicleYear: number
  • vin: string
  • accidentLocation: Address (reference from PDM)
  • damageDescription: string

Root: RenewalProcess

Data Structure:

• RenewalProcess (Process-specific type)
  • customer: Customer (reference from PDM)
  • renewalDate: date
  • premiumChange: number
  • renewalStatus: enum [“Pending Review”, “Offer Generated”, “Offer Sent”, “Accepted”, “Declined”, “Expired”]

Example use cases

• Add an attribute
• Remove a field
• Library integration

1. A configurator adds a new attribute loyaltyTier to the Customer data type in the PDM.
2. This attribute is an enum [“Bronze”, “Silver”, “Gold”, “Platinum”].
3. The new attribute automatically propagates to all processes using the Customer data type.
4. The Policy Renewal Process now has access to the customer’s loyalty tier without any process-level changes.

1. A configurator tries to remove the contactInformation attribute from the Customer data type.
2. The system displays a warning that the attribute is in use by multiple processes.
3. The configurator is prevented from making the change until the references are resolved.

1. The company uses a “Common Insurance Standards” library with standardized data types.
2. After setting the library as a dependency, they can use the library’s “Vehicle” data type in their PDM.
3. When the library updates, the configurator can choose to adopt the changes.

Benefits demonstrated

This example shows how the Project Data Model:

• Ensures data consistency: Core entities like Customer and Policy maintain consistent structures across all processes and resources.
• Promotes reusability: Common data types are defined once and reused in in multiple processes, business rules, and other resources.
• Simplifies changes: Updates to data types are propagated automatically to all processes.
• Enforces governance: Sensitive data is marked at the project level for consistent handling.
• Allows flexibility: Process-specific data can extend the PDM while maintaining core data integrity.

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Export and import

You can export and import project data types to transfer them between projects or environments.

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Exporting

To export project data types:

1. Open the context menu on the Project Data Model page
2. Select Export
3. The data types are downloaded as a ZIP file

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Importing

To import project data types:

1. Open the context menu on the Project Data Model page
2. Select Import
3. Select the ZIP file exported from another project or environment
4. If data types with the same identifiers already exist, a Review Resource Identifiers Conflicts modal appears
5. Choose a strategy for each conflicting data type (or use Apply to all):
   • Keep both - imports the data type as a new copy alongside the existing one
   • Replace - overwrites the existing data type with the imported version
   • Skip this one - keeps the existing data type unchanged
6. Click Continue to complete the import

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Best practices

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Limitations

Show Current limitations of the Project Data Model

Custom Data Types from the Project or Library Data Model level cannot be modified at the resource level.

Removing or changing Data Types in use may break resources using it.

Project Data Model becomes read-only after version commitment. This is available for any configuration on commited versions; it applies also for resources data models.

Library builds with breaking changes to Data Types require usage review.

Data Types defined at the Project or Library level can be referenced in the data models of Processes, Reusable Functions, and Reusable UI Templates.

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Troubleshooting

Cannot modify a referenced data type in process

1

Problem

You’re trying to edit a data type from the PDM within a process, but the fields are read-only.

2

Solution

Make changes at the project level instead:

1. Navigate to the Project Data Model
2. Locate and edit the data type
3. Save changes
4. The changes will propagate to all processes

Cannot delete a data type that is in use

1

Problem

You’re trying to delete a data type, but receive an error that it’s in use.

2

Solution

Either:

• Remove all references to the data type first
• Create a new version of your project to make the change

References broken after type change

1

Problem

After changing a data type (e.g., from string to number), references are broken in processes.

2

Solution

Review affected processes and update references manually:

1. Check the warning message that lists affected processes
2. Open each process
3. Update UI templates or other components that referenced the changed attribute

Library update warning about breaking changes

1

Problem

When updating a library dependency, you receive warnings about breaking changes to data types.

2

Solution

Carefully review the changes and their impact before proceeding:

1. Check which data types are affected
2. Review how these types are used in your processes
3. Decide whether to proceed with the update or maintain the current version

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