To create a diagram that contains only the Sales table and related tables, you should use the Model

view (C) in Microsoft Power BI Desktop. This view allows you to visualize and manage the

relationships between tables within your semantic model. Reference = Microsoft Power BI Desktop

documentation outlines the functionalities available in Model view for managing semantic models.

:

The measure should use the AVERAGE function to calculate the average value.

It should reference the Response Value column from the 'Survey' table.

The 'Number of months' should be used to define the period for the average calculation.

To calculate the average overall satisfaction score using DAX, you would need to use the AVERAGE

function on the response values related to satisfaction questions. The DATESINPERIOD function will

help in calculating the rolling average over the last 12 months.

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No, the EXPLAIN TABLE statement does not identify whether maintenance tasks were performed on

a table. It shows the execution plan for a query. Reference = The usage and output of the EXPLAIN

command can be found in the Spark SQL documentation.

:

To meet the requirements, developers should have Admin access to the deployment pipeline (B),

Contributor access to the Development and Test workspaces (E), and Viewer access to the

Production workspace (D). This setup ensures they can perform necessary actions in development

and test environments without having the ability to affect production. Reference = The Power BI

documentation on workspace access levels and deployment pipelines provides guidelines on

assigning appropriate permissions.

The Vertipaq Analyzer tool (B) and querying the

$system.discovered_STORAGE_TABLE_COLUMNS_IN_SEGMENTS dynamic management view (DMV)

(C) can help identify which columns are frequently loaded into memory. Both methods provide

insights into the storage and retrieval aspects of the semantic model. Reference = The Power BI

documentation on Vertipaq Analyzer and DMV queries offers detailed guidance on how to use these

tools for performance analysis.

Remove the files: Run the VACUUM command on a schedule.

Combine the files: Set the optimizeWrite table setting. or Run the OPTIMIZE command on a

schedule.

To remove files that are no longer used, the VACUUM command is used in Delta Lake to clean up

invalid files from a table. To combine smaller files into larger ones, you can either set the

optimizeWrite setting to combine files during write operations or use the OPTIMIZE command, which

is a Delta Lake operation used to compact small files into larger ones.

To reduce memory usage and refresh time, splitting the OrderDateTime into separate date and time

columns (A) can help optimize the model because date/time data types can be more memory-

intensive than separate date and time columns. Moreover, replacing TotalSalesAmount with a

measure (D) instead of a calculated column ensures that the calculation is performed at query time,

which can reduce the size of the model as the value is not stored but calculated on the fly. Reference

= The best practices for optimizing Power BI models are detailed in the Power BI documentation,

which recommends using measures for calculations that don't need to be stored and adjusting data

types to improve performance.

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When creating a shortcut to an Azure Data Lake Storage Gen2 account in a lakehouse, you should use

the abfss (Azure Blob File System Secure) connection string and the dfs (Data Lake File System)

endpoint. The abfss is used for secure access to Azure Data Lake Storage, and the dfs endpoint

indicates that the Data Lake Storage Gen2 capabilities are to be used.