Get DP-500 Dumps : Verified Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

Users indicate that queries against the serverless SQL pool fail occasionally because the size of tempdb has been exceeded.

In the dedicated SQL pool resource, temporary tables offer a performance benefit because their results are written to local rather than remote storage.

Temporary tables in serverless SQL pool.

Temporary tables in serverless SQL pool are supported but their usage is limited. They can't be used in queries which target files.

For example, you can't join a temporary table with data from files in storage. The number of temporary tables is limited to 100, and their total size is limited to 100 MB.

Step 1: Create row-level security (RLS) roles

Create roles

Note: Provide all the customers with their own Power BI workspace to create their own reports. Each workspace will use the new dataset in the FinData workspace.

Implement subscription levels for the customers. Each subscription level will provide access to specific rows of financial data.

Deploy prebuilt datasets to Power BI to simplify the query experience of the customers.

Step 2: Create a DAX expression

Consider a model with two roles: The first role, named Workers, restricts access to all Payroll table rows by using the following rule expression:

FALSE()

Note: A rule will return no table rows when its expression evaluates to false.

Yet, a second role, named Managers, allows access to all Payroll table rows by using the following rule expression:

TRUE()

Take care: Should a report user map to both roles, they'll see all Payroll table rows.

Step 3: Add members to row-level security (RLS) roles

Configure role mappings

Once [the model is] published to Power BI, you must map members to dataset roles.

Box 1: PREDICT

Provide internal users with the ability to incorporate machine learning models loaded to the dedicated SQL pool.

The example below shows a sample query using prediction function. An additional column with name Score and data type float is created containing the prediction results. All the input data columns as well as output prediction columns are available to display with the select statement.

-- Query for ML predictions

SELECT d.*, p.Score

FROM PREDICT(MODEL = (SELECT Model FROM Models WHERE Id = 1),

DATA = dbo.mytable AS d, RUNTIME = ONNX) WITH (Score float) AS p;

Box 2: WITH

Refresh data from an on-premises SQL Server database

The SQL Server database must be accessed by Power BI through an on-premises data gateway.

You can install an on-premises data gateway on the same local computer as SQL Server (in production, it would typically be a different computer).