How to Enable Scale-Out for a Semantic Model

DP-600 Last updated

Short answer

C At the semantic model level, set Large dataset storage format to On.

Question

You have a Fabric tenant that uses a Microsoft Power BI Premium capacity. You need to enable scale-out for a semantic model. What should you do first?

  1. At the semantic model level, set Large dataset storage format to Off.
  2. At the tenant level, set Create and use Metrics to Enabled.
  3. At the semantic model level, set Large dataset storage format to On. Correct Answer
  4. At the tenant level, set Data Activator to Enabled.

Key Takeaways

Enabling semantic model scale-out requires the Large dataset storage format to be turned On, as scale-out relies on premium capacity features unlocked by this storage format.

To enable scale-out for a semantic model in Power BI Premium, you must first configure the large dataset storage format. This page confirms that setting the Large dataset storage format to On at the semantic model level is the required first step.

Common mistake: Choosing a tenant-level setting like Metrics or Data Activator, confusing tenant-wide feature toggles with the prerequisite model-level storage configuration.

Expert Analysis

Why the Answer Is Correct

Enabling scale-out for a semantic model in Power BI Premium capacity requires the model to use the Large dataset storage format. Setting Large dataset storage format to On at the semantic model level is the explicit prerequisite to unlock scale-out capabilities, allowing the model to distribute query loads across multiple replicas for high concurrency.

Why the Other Options Are Wrong

Option A is incorrect because turning the Large dataset storage format Off disables the premium features necessary for scale-out. Options B and D are incorrect because Create and use Metrics and Data Activator are tenant-level settings for different Fabric features and have no bearing on semantic model scale-out prerequisites.

Community Comment Notes

Commenters unanimously agreed on option C, pointing directly to the official documentation. As Nicofr noted by providing the documentation link, the configuration guide explicitly lists the large dataset storage format as a prerequisite. Charley92 also explained that this format allows models to take advantage of premium capacity features, including scale-out capabilities.

Official Reference

Exam Strategy

For questions about semantic model features in Premium capacity, check the model-level settings first, specifically the Large dataset storage format. Remember that tenant-level admin settings govern feature availability, but model-level settings are often prerequisites for advanced premium features like scale-out.

Community Votes

C
100%

100% of anonymous learners picked answer C. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 7 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded.

From public community threads 7

  1. Nicofr 👍 17 Answered C
    https://learn.microsoft.com/en-us/power-bi/enterprise/service-premium-scale-out-configure
  2. Charley92 👍 3 Answered C
    To enable scale-out for a semantic model in Power BI Premium, the Large dataset storage format must first be turned On. This is because the large dataset storage format allows models to take advantage of premium capacity features, including scale-out capabilities, which help distribute the load across multiple replicas for high-concurrency scenarios.
  3. DarioReymago 👍 2 Answered C
    Defini...defini...definitively is C
  4. kaixin 👍 1 Answered C
    https://learn.microsoft.com/en-us/power-bi/enterprise/service-premium-scale-out "The Scale-out queries for large semantic models setting for your tenant is enabled (default)."
  5. NRezgui 👍 1 Answered C
    . At the semantic model level, set Large dataset storage format to On.
Show 2 more comments
  1. Rakesh16 👍 1 Answered C
    At the semantic model level, set Large dataset storage format to On
  2. Momoanwar 👍 1 Answered C
    Correct

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