Enable automatic scaling of Lakehouse compute resources based on workload demand, user activity, or job size, similar to Azure Synapse and Databricks autoscaling features.
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Introduce fine-grained role-based access control (RBAC) for individual items (e.g., Lakehouse, Pipeline, Notebook) within a Fabric workspace, enabling better data governance.
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Automatically organize fields into folders based on their data type, name prefix, or table origin (e.g., all “amt_” fields go into “Amounts”).
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Support shared measure libraries that can be reused across multiple semantic models and workspaces, reducing duplication and ensuring consistency in KPIs.
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Trigger alerts or filters in the mobile app based on geolocation, such as alerting a store manager about KPIs when they enter a specific branch location.
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Allow display folders in semantic models to be generated or rearranged dynamically based on table type, naming convention, or user preference.
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Allow relationships to be defined across data domains (e.g., between tables in Lakehouse and Warehouse) within the same semantic model, without needing to duplicate data.
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Add a built-in tool to test semantic model performance, with scoring for refresh speed, DAX complexity, and table size, along with recommendations for improvement.
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