Collibra includes a number of out-of-the-box attribute types that provide a strong foundation upon which you can build your specific data governance models. They cover the most common needs and allow you to focus your customization efforts on the unique aspects of your data landscape, rather than reinventing essential metadata elements.
You can find all attribute types in the Attribute types table in the Operating Model settings.
- The System Managed column indicates whether an item is provided out of the box (OOTB) and managed by Collibra. All system-managed items are OOTB, but not all OOTB items are system-managed. The green checkmark icon (
) in the column means that the item is managed by Collibra, whereas the red cross icon (
) means that the item is either user-created or an editable OOTB item. - To find which asset types use a specific item, select the row containing the item and click Used In.
The following table contains out-of-the-box attribute types.
| Name | Description | Assigned asset types | Kind | Public ID |
|---|---|---|---|---|
|
1st Decile |
Value below which 10% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
FirstDecile |
|
1st Percentile |
Value below which 1% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
FirstPercentile |
|
1st Quartile |
Value below which 25% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
FirstQuartile |
|
3rd Quartile |
Value below which 75% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
ThirdQuantile |
|
5th Percentile |
Value below which 5% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
FifthPercentile |
|
95th Percentile |
Value below which 95% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
NinetyFifthPercentile |
|
99th Percentile |
Value below which 99% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
LastPercentile |
|
9th Decile |
Value below which 90% of the data falls, when the data is sorted from smallest to largest. |
Column |
Text |
LastDecile |
| Abbreviation | Shorthand signifier for an asset. | Report | Text | Abbreviation |
| Access Instructions | Instructions on how to access the data. | AI Endpoint, Data Product Port | Text | AccessInstructions |
| Access Method | Indicates what method can be used to access the data. | AI Endpoint, Data Product Port | Selection | AccessMethod |
| Alert Configuration | Defines the threshold conditions that trigger an alert and the communication channels (e.g., email, Slack) used to notify stakeholders. | AI Monitor | Text | AlertConfiguration |
| Analysis | Analysis of this issue. | Issue | Text | Analysis |
| Application Regulation | Any regulations that apply to the application. For example, for certain applications that consume data, there is a regulation about how to handle that. | Directory, System, Technology Asset | Text | ApplicationRegulation |
| Application Standards | Any standards applied to the business application. | Directory, System, Technology Asset | Text | ApplicationStandards |
| Approval Date | Date when the assessment was approved. | Assessment Review | Date | ApprovalDate |
| Area | Geographical area or location where the data was collected or generated. | SAP Data Product | Text | Area |
| Assessment Link | Link to the submitted assessment. | Assessment Review | Text | AssessmentLink |
| Automation Level | Nature and degree of automation of an AI use case. | AI Use Case | Text | AutomationLevel |
| Background | Background information on the asset. | N/A | Text | Background |
| Business Case | Business problem you want to solve with an AI use case. | AI Use Case, Data Product, SAP Data Product | Text | BusinessCase |
| Business Name | Descriptive label to represent an asset in business terminology. | Column, Database View, SAP Datasphere Analytic Model, SAP Datasphere Data Attribute, SAP Datasphere Intelligent Lookup, SAP Datasphere Perspective, Table | Text | BusinessName |
| Business Risks | Summary of the business risks associated with implementing the AI use case. | AI Use Case | Text | BusinessRisks |
| Business Value | Refers to how an AI use case can improve your organization. | AI Use Case | Text | BusinessValue |
| Business Sponsor | Business Owner or Executive Sponsor of the AI use case in your organization. | AI Use Case | Text | BusinessSponsor |
| Calculation Rule | Rule that specifies how the KPI or metric is calculated. | KPI, Tableau Report Attribute | Text | CalculationRule |
|
Categorical Data |
Data is considered categorical if it can take only a limited set of different values. |
Column |
True/False |
CategoricalData |
|
Category |
Possible value for Categorical Data. |
Column |
Text |
Category |
|
Certified |
Indicates if a report asset meets the set standards. |
Data Set, Looker Dashboard, Looker Data Set, Looker Look, Looker Tile, Power BI Dashboard, Power BI Data Model, Power BI Report, Power BI Tile, Tableau Data Model |
True/False |
Certified |
|
Char Octet Length |
For character types, the maximum number of bytes in the column. |
Column |
Number |
CharOctetLength |
|
Column Position |
Index of the column in the table. |
Column |
Number |
ColumnPosition |
| Compute Configuration | Shows the capacity and amount of resources allocated to this asset. | AI Model Deployment | Text | ComputeConfiguration |
|
Conformity Score |
Amount of rows that passed the rule. |
Business Rule, Data Quality Metric |
Number |
ConformityScore |
|
Co-role |
Relationship name from tail to head. |
N/A |
Text |
CoRole |
| Creation Date in Source | The date on which the resource was created in the source system. | AI Agent, AI Base Model, AI Model Deployment | Date | CreationDateInSource |
|
Criticality Indicator |
Criticality of an asset. |
N/A |
True/False |
CriticalityIndicator |
| Data Drift Detection Enabled | Data drift detection monitors shifts in input data distributions over time to identify when a model’s environment no longer matches its training data. This attribute type captures whether data drift detection is enabled on the AI Monitor. | AI Monitor |
True/False |
DataDriftDetection |
| Data Privacy Risk Score | Number calculated from Risk Assessment. | AI Use Case | Number | DataPrivacyRiskScore |
| Data Privacy Risks | Any data privacy risks that may result from processing the AI model within the context of this AI use case and either putting it on the market for external customer use or internal use. | AI Use Case | Text | DataPrivacyRisks |
| Data Product Category | Helps categorizing the data products in, for example, more business user specific derived data products, versus more technical/foundational base data products targeted at the more technical users that are building the derived data products. | Data Product | Selection | DataProductCategory |
| Data Retention Protocols | Any data retention standards already in place or projected to be implemented for the AI use case. | AI Use Case | Text | DataRetentionProtocols |
| Data Source | Data source of an asset. It specifies where the data corresponding to this asset is coming from. | Database, Tableau Data Model, Schema | Text | DataSource |
|
Data Source Type |
Type of the registered data source. |
Schema, Database |
Selection |
DataSourceType |
| Data Storage | Refers to whether any data is stored, and if so, where and how the data is stored. | AI Use Case | Text | DataStorage |
| Data Type | Logical Data type detected by Collibra profiling. | Column | Text | DataType |
| Data Type Precision | Precision of the data type, for example, how many characters it can contain. | Data Attribute, Data Element, Report Attribute | Number | DataTypePrecision |
|
Date and/or Time Pattern |
Pattern used to encode a time, date, or both. Format must be compatible with a java DateTimeFormatter, for example, |
Column |
Text |
DateAndOrTimePattern |
|
Default Value |
Default value for the column. |
Column |
Text |
DefaultValue |
| Definition | Shortest possible description that clearly defines the purpose of the asset. | Business Asset, Business Process, Business Term, Data Category, KPI, Line of Business, Measure, Report, Report Attribute | Text | Definition |
| Description | Description of the asset. This is typically a more verbose way to describe what the asset means. |
Asset, AI Base Model, AI Model Deployment, AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Foundry Agent, Azure AI Model Version, Azure AI Foundry Model Version, Business Dimension, Business Rule, Code Set, Code Value, Column, Crosswalk, Data Asset, Data Attribute, Database, Data Element, Data Entity, Data Model, Data Quality Dimension, Data Quality Metric, Data Quality Rule, Data Set, Data Sharing Agreement, Data Structure, Data Usage, Directory, File, File Group, Governance Asset, Issue, Issue Category, Looker Dashboard, Looker Data Set, Looker Data Set Column, Looker Folder, Looker Look, Looker Query, Looker Report Attribute, Looker Tenant, Looker Tile, Mapping Specification, MLflow AI Model Version, Policy, Power BI Capacity, Power BI Dashboard, Power BI Data Model, Power BI Table, Power BI Column, Power BI Report, Power BI Server, Power BI Tile, Power BI Workspace, Report, Report Attribute, Role Type, Rule, S3 Bucket, S3 File System, SAP AI Model Version, Schema, Standard, System, Table, Tableau Data Source, Tableau Project, Tableau Report Attribute, Tableau Server, Tableau Site, Tableau View, Tableau Workbook, Technology Asset, Validation Rule, Workflow Definition, Dataplex Lake, Dataplex Zone, Databricks AI Model Version, Vertex AI Model Version, Data Product |
Text | Description |
| Description From Source System | Description from the source system of the asset. | AI Agent, AI Base Model, AI Model Version, Table, Column, Database, Schema, Dataplex Lake, Dataplex Zone, Databricks AI Model Version | Text | DescriptionFromSourceSystem |
| Descriptive Example | Example of the asset. | Asset, Business Asset, Business Process, Business Rule, Business Term, Code Set, Code Value, Data Asset, Data Attribute, Data Category, Data Element, Data Entity, Data Model, Data Quality Metric, Data Quality Rule, Data Structure, Directory, Governance Asset, Issue Category, KPI, Line of Business, Measure, Policy, Report, Role Type, Rule, Standard, System, Technology Asset | Text | DescriptiveExample |
|
Document creation date |
Date when the document was created. |
Azure AI Foundry Agent, Looker Dashboard, Looker Folder, Looker Look, SAP AI Model Version, Tableau Data Source, Tableau View, Tableau Workbook |
Date |
DocumentCreationDate |
|
Document last accessed date |
Date when the document was last accessed. |
Looker Dashboard, Looker Look |
Date |
DocumentLastAccessedDate_C |
|
Document last viewed date |
Date when the document was last viewed. |
Looker Dashboard, Looker Look |
Date |
DocumentLastViewedDate_C |
|
Document modification date |
Date when the document was last edited. |
Looker Look, SAP AI Model Version, Tableau Data Source, Tableau View, Tableau Workbook |
Date |
DocumentModificationDate |
|
Document size |
Size of the document in megabytes. |
File, File Group, Tableau Workbook |
Number |
DocumentSize |
| Effective End Date | Date when the asset is scheduled to end. | Business Rule, Code Set, Code Value, Data Quality Metric, Data Quality Rule, Data Usage, Governance Asset, Issue Category, Policy, Rule | Date | EffectiveEndDate |
|
Effective Start Date |
Date when the asset takes effect. |
Business Rule, Code Set, Code Value, Data Quality Metric, Data Quality Rule, Data Usage, Governance Asset, Issue Category, Policy, Rule |
Date |
EffectiveStartDate |
|
Empty Values Count |
Number of empty values for that column. |
Column |
Number |
EmptyValuesCount |
|
Empty values definition override |
Overrides the default list of values to consider as empty or missing values during data profiling. It must be a comma-separated list of text values with each value enclosed in double quotes. |
Column, Schema, Table |
Text |
EmptyValuesDefinitionOverride |
| Entity Load Date | Load date of the entities from the external system. | Data Quality Metric | Text | EntityLoadDate |
| Ethical Risks | Any ethical risks that may result from processing the AI model within the context of this AI use case and either putting it on the market for external customer use or internal use. | AI Use Case | Text | EthicalRisks |
| Exception Scenario |
Defines when data is handled differently or excluded. |
Business Rule, Data Quality Metric, Data Quality Rule, Data Sharing Agreement, Governance Asset, Issue Category, Policy, Rule, Standard |
Text | ExceptionScenario |
| External System Label | Label from external system. | File, GCS Bucket, Storage Container | Text | ExternalSystemLabel |
|
Favorites count |
Number of Looker Looks and Looker Dashboards that are marked as favorite. |
Looker Dashboard, Looker Look |
Number |
FavoritesCount |
| Feature Importance | Refers to how important a feature is to a machine learning model. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Text | FeatureImportance |
|
File Location |
Location of the original source file. |
File, Schema |
Text |
FileLocation |
|
File Type |
Type of a File, which may constrain its format, its content, or both. |
File, File Group |
Text |
FileType |
|
Foreign Key Delete Rule |
Indicates what happens to the foreign key when primary is deleted. |
Foreign Key |
Text |
ForeignKeyDeleteRule |
| Foreign Key Evaluation Deferrability | Indicates if the evaluation of the foreign key constraints be deferred until commit. |
Foreign Key |
Text |
ForeignKeyEvaluationDeferrability |
|
Foreign Key Update Rule |
Indicates what happens to foreign key when primary is updated. |
Foreign Key |
Text |
ForeignKeyUpdateRule |
| Framework | The machine learning framework used to build the model. | AI Model Version |
Text |
Framework |
|
Frequency |
Rate at which an asset changes over a particular period of time. |
Report, Report Attribute |
Text |
Frequency |
| General Purpose AI | Indicates if the model used in your AI use case is using a General Purpose AI (GPAI). | AI Use Case | Text | GeneralPurposeAI |
| Glue Database Name | Name of the AWS Glue database in which this data is referenced and described. | Table | Text | GlueDatabaseName |
| Glue Table Name | Name of the AWS Glue table in which this data is referenced and described. | Table | Text | GlueTableName |
| Implemented Content Filtering | List the content filters activated on an AI Model deployment, to avoid unwanted output being generated. | AI Model Deployment | Text | ImplementedContentFiltering |
|
Inclusion Scenario |
Defines when data is considered for inclusion. |
Business Rule, Data Quality Metric, Data Quality Rule, Data Usage, Governance Asset, Issue Category, Policy, Report, Report Attribute, Rule, Standard |
Text |
InclusionScenario |
| Industry | Specific industry or sector that the data product is relevant to. | SAP Data Product | Text | Industry |
| Inference Data Description | Explanation of the input or inference data the AI model(s) uses to create output data. | AI Use Case | Text | InferenceDataDescription |
| Inferred Data Type | Data type of a data asset that was automatically inferred by profiling corresponding instance data. | N/A | Text | InferredDataType |
| Initiating User in Source | Shows the name of the user who initiated the creation of this resouce in the source system. We capture this as an attribute and not via responsibilities because the user who has an account in the source system may not have a Collibra user. | AI Model Deployment | Text | InitiatingUserInSource |
| Instructions | A set of guidelines, rules, or commands that define how an AI model, agent, or assistant should behave or respond. | Azure AI Foundry Agent | Text | Instructions |
| Intellectual Property Risks | Inherent Intellectual Property Risks resulting from processing AI Models within this use case and placing them on the market or putting into service for own use. | AI Use Case | Text | IntellectualPropertyRisks |
| Internal Model | Existing or upcoming internally built model(s) your AI use case may use. | AI Use Case | Text | InternalModel |
|
Is Auto Incremented |
Indicates if this column is automatically incremented. |
Column |
True/False | IsAutoIncremented |
|
Is Generated |
Indicates if this is a generated column. |
Column |
True/False | IsGenerated |
|
Is Mandatory |
Indicates if the asset is mandatory or not. |
Data Attribute |
True/False | IsMandatory |
|
Is Nullable |
Indicates if the column can store NULL values. |
Column |
True/False | IsNullable |
| Is Primary Key | Indicates if the column is a primary key. | Column | True/False | IsPrimaryKey |
| Is Unique | Indicates if the asset is unique or not. | Data Attribute | True/False | IsUnique |
| IT Requirements | Requirements from an IT perspective for the asset. | Crosswalk, Mapping Specification | Text | ITRequirements |
| Key sequence | Key sequence of an element in a foreign key. | N/A | Number | KeySequence |
| Labels | User-defined labels in Dataplex. | Dataplex Zone, Dataplex Lake | Text | Labels |
| Lake Id | ID of the Dataplex lake. | Dataplex Lake | Text | LakeId |
| Lake Status | Current state of the Dataplex lake. | Dataplex Lake | Text | LakeStatus |
|
Last Review Date |
Date when the asset was last reviewed. |
Code Set, Data Usage, Report, Report Attribute, Standard |
Date |
LastReviewDate |
|
Last Sync Date |
Date when the asset was synchronized with external system. |
Code Set, Code Value, Database, Data Quality Metric, File |
Date |
LastSyncDate |
| Legal Approval Date | Date when your legal team approved or rejected the AI use case. | AI Use Case | Date | LegalApprovalDate |
| Legal Approval Renewal Date | Date of the expected periodical review of the AI use case’s approval. | AI Use Case | Date | LegalApprovalRenewalDate |
| Legal Description of Model | Description of the AI model provided by your legal team. | AI Use Case | Text | LegalModelDescription |
|
License |
Current license. |
Data Set |
Text |
License |
|
Loaded Rows |
Number of rows that were loaded. |
Business Rule, Data Quality Metric |
Number |
LoadedRows |
|
Loaded Values |
Number of values that were loaded. |
N/A |
Number |
LoadedValues |
| Load Sample | Sample. | N/A | Text | LoadSample |
| Location | Location where the actual asset is stored or can be found. | Asset, Code Set, Code Value, Data Asset, Data Attribute, Database, Data Element, Data Entity, Data Model, Data Structure, Directory, Report, Report Attribute, Role Type, S3 Bucket, System, Technology Asset, Dataplex Zone, Dataplex Lake | Text | Location |
| Maintenance Cost | Overall expected cost of running the AI use case over a selected period of time. | AI Use Case | Text | MaintenanceCost |
| Materiality |
Importance of data in a given context. |
Data Usage | Text | Materiality |
|
Maximum Text Length |
Length of the longest text value in this column. |
Column |
Number |
MaximumTextLength |
|
Maximum Value |
Maximum value, using alphabetical order for text. |
Column |
Text |
MaximumValue |
| Max Length | Maximum length of any value corresponding to the data asset. | N/A | Number | MaxLength |
|
Mean |
Mean of values (numeric only), excluding missing values |
Column |
Number |
Mean |
| Mean Absolute Error | Model quality metric that evaluates the performance of regression models. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Number | MeanAbsoluteError |
| Mean Squared Error | Model quality metric that measures the quality of the model’s predications. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Number | MeanSquaredError |
| Measurement | Measurement of the asset. | Business Rule, Data Quality Rule, Governance Asset, Issue Category, Policy, Rule | Number | Measurement |
|
Median |
Data median value. |
Column |
Text |
Median |
|
Minimum Text Length |
Length of the shortest text value in this column. |
Column |
Number |
MinimumTextLength |
|
Minimum Value |
Minimum value, using alphabetical order for text. |
Column |
Text |
MinimumValue |
| Min Length | Minimum length of any value corresponding to the data asset. | N/A | Number | MinLength |
|
Mode |
Value with the highest frequency for a categorical feature. |
Column |
Text |
Mode |
| Model Accuracy | Refers to how well the model performs on a given task. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Text | ModelAccuracy |
| Model Monitoring | Refers to how your organization will ensure an AI model is meeting accuracy and performance expectations. | AI Use Case | Text | ModelMonitoring |
| Model Output | Explanation of the output data that the AI model(s) is expected to create. | AI Use Case | Text | ModelOutput |
| Model Precision | Refers to how accurate positive model predictions are. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Text | ModelPrecision |
| Model Type | Type of AI model. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Selection | ModelType |
| Modification Date in Source | The date on which the resource was modified in the source system. | AI Model Deployment | Date | ModificationDateInSource |
|
Non Conformity Score |
Amount of rows that failed the rule. |
Business Rule, Data Quality Metric |
Number |
NonConformityScore |
| Note | Note. |
Asset, Business Asset, Business Process, Business Rule, Business Term, Code Set, Code Value, Data Asset, Data Attribute, Database, Data Category, Data Element, Data Entity, Data Model, Data Quality Rule, Data Structure, Directory, File, KPI, Line of Business, Measure, Policy, Report Attribute, Role Type, Standard, System, Technology Asset |
Text | Note |
| Null Count | Number of null values in the data corresponding to the data asset. | N/A | Number | NullCount |
| Number of Attributes | Number of attributes of the data entity. | N/A | Number | NumberOfAttributes |
|
Number of distinct values |
Number of different values stored in this column. |
Column |
Number |
NumberOfDistinctValues |
|
Number of Files |
Number of files in a file group. |
File Group |
Number |
NumberOfFiles |
|
Number Of Fractional Digits |
Number of fractional digits. |
Column |
Number |
NumberOfFractionalDigits |
| Number of Values | Number of distinct instance values in the data corresponding to the data asset. | N/A | Number | NumberOfValues |
|
Original Name |
Name of this object in its source environment. The original name may differ from the asset's name in Data Governance Center. |
Column, Tableau Data Source, Tableau Project, Tableau Report Attribute, Tableau Site, Tableau View, Tableau Workbook |
Text |
OriginalName |
| Other Risks | Other risks resulting from processing AI Models within this use case and placing them on the market or putting into service for own use. | AI Use Case | Text | OtherRisks |
| Overall Risk Analysis | Details and the result of any risk analysis performed on the AI use case. | AI Use Case | Text | OverallRiskAnalysis |
| Overall Risk Rating | Risk level calculated based on predefined thresholds in the default Risk Assessment. | AI Use Case | Selection | OverallRiskRating |
| Owner in Source | Email address of the owner of the data objects in a data source, represented in Collibra by the asset types mentioned here. | AI Base Model, Looker Dashboard, Looker Folder, Looker Look, Power BI Data Model, Power BI Report, Power BI Workspace, Tableau Project, Tableau Data Model, Tableau Workbook, Tableau Dashboard, Database, Schema, Table, Database View | Text | OwnerInSource |
| Passing Fraction | Percentage of rows or entities that have passed the rule. | Business Rule, Data Quality Metric | Number | PassingFraction |
|
Personally Identifiable Information |
Indicator to flag an asset that could potentially be used to identify a specific individual. |
Column |
True/False |
PersonallyIdentifiableInformation |
| Predicate | Logical formula that will be run to implement the rule. | Data Quality Rule | Text | Predicate |
| Prediction Drift Detection Enabled | Tracks changes in the model’s output distribution to identify shifts in prediction patterns, serving as an early warning for model decay when actual outcomes are delayed. This attribute type captures whether prediction drift detection is enabled on the AI Monitor. | AI Monitor |
True/False |
PredictionDriftDetection |
| Pricing | Financial cost associated with accessing and utilizing a specific data or a service. It defines the terms of service, including subscription fees, usage-based charges, or other pricing models. | SAP Data Product | Text | Pricing |
|
Primary Key Name |
Name of the primary key composed by the column. |
Column |
Text |
PrimaryKeyName |
| Priority | Priority of the issue. | Issue | Text | Priority |
| Profiled Row Count | Number of rows from the data set that were selected for profiling. | N/A | Number | ProfiledRowCount |
|
Profiling Information |
Additional information about the status of the profiling results. |
Table |
Text |
ProfilingInformation |
| Project Id | Globally unique identifier for your Google Cloud Platform project. | GCP Project | Text | ProjectId |
| Project Number | Automatically generated unique identifier for the Google Cloud Platform project. | GCP Project | Number | ProjectNumber |
| Protective Measures | Any additional required or recommended actions that have been identified based on regulations, industry standards, or dedicated frameworks. | AI Use Case | Text | ProtectiveMeasures |
| Purpose | Reason that the asset exists. | Business Rule, Data Sharing Agreement, Data Usage, File, Governance Asset, Issue Category, Policy, Rule, Standard | Text | Purpose |
|
Rating |
Current rating. |
N/A |
Number |
Rating |
|
Refresh Conflict |
Information about the conflict detected on the Data Asset during a Schema refresh if any. |
Column, Table |
Text |
RefreshConflict |
|
Refresh Frequency |
Frequency of refresh. |
N/A |
Text |
RefreshFrequency |
|
Report Image |
Image of the report view. |
Looker Look, Tableau View, Tableau Workbook |
Text |
ReportImage |
| Repository | Reference to the repository where the code behind the model is stored. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Text | Repository |
| Request Rate Limit | Maximum number of API requests that are allowed per minute. | Azure AI Foundry Model Version | Number | RequestRateLimit |
| Required Content Filtering | Defines the criteria or rules that need to be applied to restrict, refine, or control the type of content generated by an AI Model. | AI Base Model, AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, SAP AI Model Version, Vertex AI Model Version | Text | ContentFilter |
| Resolution | Solution of how this issue can or is resolved. | Issue | Text | Resolution |
| Result | Outcome. | Business Rule, Data Quality Metric | True/False | Result |
| Retirement Date in Source | The date on which the resource was retired in the source system. | AI Base Model, AI Model Deployment | Date | RetirementDateInSource |
| Retrain Cycle | Frequency with which the model is retrained. | AI Base Model | Text | RetrainCycle |
|
Role |
Relationship name from head to tail. |
N/A |
Text |
Role |
|
Role in Report |
Use of Report Attribute in Report (for example, measure or dimension) |
Tableau Report Attribute |
Text |
RoleInReport |
|
Row Count |
Number of rows inside the data set, possibly including duplicated or missing values |
Column |
Number |
RowCount |
|
Rows Failed |
Amount of rows that failed the rule. |
Data Quality Metric |
Number |
RowsFailed |
| Rows Passed | Amount of rows that passed the rule. | Data Quality Metric | Number | RowsPassed |
| Rule | Description of the rule. | N/A | Text | Rule |
| Rule Status | Status of the rule. | Breaking, Passing, Active, Learning, Suppressed, NA, Deleted | Text | RuleStatus |
| Safeguard Effectiveness | Overall safeguard effectiveness calculated based on pre-defined thresholds in the default Risks and Safeguards Assessment. | AI Use Case | Selection | SafeguardEffectiveness |
| Schedule | Defines the frequency (e.g., hourly, daily) at which a monitor analyzes data or a job is executed. | AI Monitor | Text | Schedule |
| Schema Name | Name of the schema. | N/A | Text | SchemaName |
|
Scope |
Scope of applications that correspond to this policy. |
Crosswalk, Database, Data Usage, Directory, Mapping Specification, Policy, Report, Report Attribute, System, Technology Asset |
Text |
Scope |
| Security Classification | Classification of assets based on sensitivity. | Column, Data Usage, Report, Report Attribute | Text | SecurityClassification |
| Security Protocols | Any general security protocols that may result from the implementation of the AI use case. | AI Use Case | Text | SecurityProtocols |
| Sequence Number | Sequence number of the asset, often used to order assets in a specific way. | Data Attribute | Number | SequenceNumber |
|
Size |
Size of the column in the table. |
Column |
Number |
Size |
| Source Type | Source type of an asset. | N/A | Text | SourceType |
| Source Tags | Tags assigned to the asset in the source system. | Database, Schema, Table, Database View, Column | Text | SourceTags |
|
Standard Deviation |
Statistical standard deviation of values (numeric only). |
Column |
Number |
StandardDeviation |
| Start Date | Date when the assessment was started. | Assessment Review | Date | StartDate |
| State | Current state. | N/A | Text | State |
| State Changed by | Cause of the state change. | Power BI Workspace | Text | StateChangedBy |
| State Changed Date | Date when the state was changed. | Data Sharing Agreement | Text | StateChangedDate |
| Submission Date | Date when the assessment was submitted. | Assessment Review | Date | SubmissionDate |
| Supported Input Modalities | Specifies the fundamental types of input data the model can accept. This includes discrete categories such as Text, Image, Audio, Video, or Tabular data. For multimodal models, this attribute defines the valid combinations of these inputs (e.g., Text + Image for a Visual Question Answering model). | AI Model Version | Text | SupportedInputModalities |
| Supported Model Customizations | Defines the available pathways for adapting the model's base capabilities to specific use cases. This attribute details the supported adaptation techniques (such as Full Fine-Tuning, Parameter-Efficient Fine-Tuning (PEFT), or Distillation) and the degree of structural flexibility allowed (e.g., modular adapters or freezing specific layers). It serves as a guide for developers to understand the trade-offs between computational cost and model specialization. | AI Model Version | Text | SupportedModelCustomizations |
| Supported Output Modalities | Specifies the fundamental types of output data the model can generate. This includes discrete categories such as Text, Image, Audio, Video, or Tabular data. For multimodal models, this attribute defines the valid combinations of these inputs (e.g., Text + Image for a Visual Question Answering model). | AI Model Version | Text | SupportedOutputModalities |
|
Synchronization Status |
Information about the status of the Schema synchronization. |
Schema |
Text |
SynchronizationStatus |
|
Table Type |
Table type that is declared in the data source, for example, TABLE and VIEW. |
Table |
Text |
TableType |
| Target delivery date | Date when the requested resource must be made available. | Data Product, Data Product Port | Date | TargetDeliveryDate |
|
Technical Data Type |
Data Type of a data asset as it is declared by the data source, for example, Text, Integer, Varchar, Blob, and Boolean. |
Column, Data Attribute, Data Element, Report Attribute, Power BI Column, Tableau Report Attribute |
Text |
TechnicalDataType |
| Third Party Model | Vendor of your AI model(s) and what kind of model you are using. | AI Use Case | Text | ThirdPartyModel |
| Threshold | Minimum percentage of all rows or entities that must pass the rule. | Data Quality Metric | Number | Threshold |
| Token Rate Limit | Maximum number of tokens that can be processed by the API per minute. | Azure AI Foundry Model Version | Number | TokenRateLimit |
| Tool Usage | Indicates which tools or skills the agent is allowed to use. | AI Agent | Text | ToolUsage |
| Traffic Split | Reflects how the traffic that is sent to an endpoint is split between different deployments. | AI Endpoint | Text | TrafficSplit |
| Training Data Description | Training or re-retraining data used to teach the AI model(s). | AI Use Case | Text | TrainingDataDescription |
|
Transformation Logic |
Operations or processes applied to transform data from its original state to the required format or structure. |
N/A |
Text |
TransformationLogic_C |
| Transparency Disclosure Requirements | Identified requirements, if any, for AI use case transparency. | AI Use Case | Text | TransparencyDisclosureRequirements |
|
URL |
Uniform Resource Locator, also colloquially known as web address. |
Directory, File, File Group, Looker Look, S3 Bucket, Table, Tableau Server, Tableau Site, Tableau View, Dataplex Lake, Dataplex Zone, Database View SAP AI Model Version |
Text |
Url |
| Use Case Application | Indicates that the AI use case will be used by an external audience or internally by your organization. | AI Use Case | Text | UseCaseApplication |
| Validation Result | Results of validation. | N/A | True/False | ValidationResult |
| Validation Script | Validation logic to evaluate the content of an asset. | Validation Rule | Script | ValidationScript |
| Value Distribution | Distribution percentage of the values. | N/A | Number | ValueDistribution |
|
Variance |
Statistical variance of values (numeric only). |
Column |
Number |
Variance |
| Version | A label or identifier that represents a specific state or iteration, used to track changes over time. | AI Model Version, AWS Bedrock AI Model Version, AWS Sagemaker AI Model Version, Azure AI Model Version, Azure AI Foundry Model Version, Databricks AI Model Version, MLflow AI Model Version, Vertex AI Model Version | Text | Version |
|
Visible on server |
Worksheet is uploaded to Tableau server. |
Tableau View |
True/False |
VisibleOnServer |
|
Visits count |
Number of visits on Tableau report. |
Looker Dashboard, Looker Look, Tableau View, Tableau Dashboard, Tableau Workbook, Tableau Worksheet |
Number |
VisitsCount |
|
Weighting Factor |
Factor by which some quantity is multiplied to make it comparable with others. |
N/A |
Number |
WeightingFactor |
| Zone Name | Relative resource name of a Dataplex zone in the following format: projects/{project_number}/locations/{location_id}/lakes/{lake_id}/zones/{zone_id}. |
Dataplex Zone | Text | ZoneName |