You have a deployment pipeline for a Power BI workspace. The workspace contains two datasets that use import storage mode.
A database administrator reports a drastic increase in the number of queries sent from the Power BI service to an Azure SQL database since the creation of the deployment pipeline.
An investigation into the issue identifies the following:
One of the datasets is larger than 1 GB and has a fact table that contains more than 500 million rows.
When publishing dataset changes to development, test, or production pipelines, a refresh is triggered against the entire dataset.
You need to recommend a solution to reduce the size of the queries sent to the database when the dataset changes are published to development, test, or production.
What should you recommend?
- Turn off auto refresh when publishing the dataset changes to the Power BI service.
- In the dataset, change the fact table from an import table to a hybrid table.
- Enable the large dataset storage format for workspace.
- Create a dataset parameter to reduce the fact table row count in the development and test pipelines.
Answer(s): B
Explanation:
Hybrid tables
Hybrid tables are tables with incremental refresh that can have both import and direct query partitions. During a clean deployment, both the refresh policy and the hybrid table partitions are copied. When deploying to a pipeline stage that already has hybrid table partitions, only the refresh policy is copied. To update the partitions, refresh the table.
Refreshes are faster - Only the most recent data that has changed needs to be refreshed.
Incorrect:
Not D: A dataset parameter does not reduce fact table row count.
Note: Microsoft recommends using parameters to store connection details such as instance names and database names, instead of using a static connection string.
Parameters have additional uses, such as making changes to queries, filters, and the text displayed in the report.
Reference:
https://docs.microsoft.com/en-us/power-bi/create-reports/deployment-pipelines-best-practices
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