Microsoft DP-500 Dumps

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

Build a new dataset in the FinData workspace by using data from the Synapse Analytics dedicated SQL pool.

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

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).

Users indicate that the data in Power BI reports is stale. You discover that the refresh process of the Power BI model occasionally times out.

With Query Diagnostics, you can achieve a better understanding of what Power Query is doing at authoring and at refresh time in Power BI Desktop. While we'll be expanding on this feature in the future, including adding the ability to use it during full refreshes, at this time you can use it to understand what sort of queries you're emitting, what slowdowns you might run into during authoring refresh, and what kind of background events are happening.

Some users indicate that the visuals in Power BI reports are slow to render when making filter selections.

B: You can investigate a slow query in a Power BI report using DAX Studio, looking at the query plan and the server timings.

D: Use Power BI Desktop Performance Analyzer to optimize the report or model.

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.

Tab order is the order in which users interact with the items on a page using the keyboard. Generally, we want tab order to be predictable and to closely match the visual order on the page (unless there is a good reason to deviate).

Note: If you are using the keyboard to navigate in a Power BI report, the order in which you arrive at visuals will not follow your vision unless you set the new tab order property. If you have low or no vision, this becomes an even bigger issue because you may not be able to see that you are navigating visuals out of visual order because the screen reader just reads whatever comes next.

Scan same-tenant Power BI using Azure IR and Managed Identity in public network.

Make sure Power BI and Microsoft Purview accounts are in the same tenant.

Make sure Power BI tenant Id is entered correctly during the registration.

From Azure portal, validate if Microsoft Purview account Network is set to public access.

From Power BI tenant Admin Portal, make sure Power BI tenant is configured to allow public network.

(D) In Azure Active Directory tenant, create a security group.

From Azure Active Directory tenant, make sure Microsoft Purview account MSI is member of the new security group.

On the Power BI Tenant Admin portal, validate if Allow service principals to use read-only Power BI admin APIs is enabled for the new security group.

Associate the security group with Power BI tenant

Log into the Power BI admin portal.

Select the Tenant settings page.

(C) Select Admin API settings > Allow service principals to use read-only Power BI admin APIs (Preview).

Select Specific security groups.

Select Admin API settings > Enhance admin APIs responses with detailed metadata > Enable the toggle to allow Microsoft Purview Data Map automatically discover the detailed metadata of Power BI datasets as part of its scans.

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.

Themes, contrast and colorblind-friendly colors.

You should ensure that your reports have enough contrast between text and any background colors.

Certain color combinations are particularly difficult for users with color vision deficiencies to distinguish. These include the following combinations:

green and red

green and brown

blue and purple

green and blue

light green and yellow

blue and grey

green and grey

green and black

Avoid using these colors together in a chart, or on the same report page.

Enable large datasets

Steps here describe enabling large datasets for a new model published to the service. For existing datasets, only step 3 is necessary.

Create a model in Power BI Desktop. If your dataset will become larger and progressively consume more memory, be sure to configure Incremental refresh.

Publish the model as a dataset to the service.

In the service > dataset > Settings, expand Large dataset storage format, set the slider to On, and then select Apply.

Enable large dataset slider

Invoke a refresh to load historical data based on the incremental refresh policy. The first refresh could take a while to load the history. Subsequent refreshes should be faster, depending on your incremental refresh policy.

Query Parquet files using serverless SQL pool in Azure Synapse Analytics.

Important

Ensure you are using a UTF-8 database collation (for example Latin1_General_100_BIN2_UTF8) because string values in PARQUET files are encoded using UTF-8 encoding. A mismatch between the text encoding in the PARQUET file and the collation may cause unexpected conversion errors. You can easily change the default collation of the current database using the following T-SQL statement: alter database current collate Latin1_General_100_BIN2_UTF8'.

Note: If you use the Latin1_General_100_BIN2_UTF8 collation you will get an additional performance boost compared to the other collations. The Latin1_General_100_BIN2_UTF8 collation is compatible with parquet string sorting rules. The SQL pool is able to eliminate some parts of the parquet files that will not contain data needed in the queries (file/column-segment pruning). If you use other collations, all data from the parquet files will be loaded into Synapse SQL and the filtering is happening within the SQL process. The Latin1_General_100_BIN2_UTF8 collation has additional performance optimization that works only for parquet and CosmosDB. The downside is that you lose fine-grained comparison rules like case insensitivity.

Allow sales managers to perform ad hoc sales reporting with minimal effort

Power BI report templates contain the following information from the report from which they were generated:

Report pages, visuals, and other visual elements

The data model definition, including the schema, relationships, measures, and other model definition items

All query definitions, such as queries, Query Parameters, and other query elements

What is not included in templates is the report's data.

Report templates use the file extension .PBIT (compare to Power BI Desktop reports, which use the .PBIX extension).

Note: With Power BI Desktop, you can create compelling reports that share insights across your entire organization. With Power BI Desktop templates, you can streamline your work by creating a report template, based on an existing template, which you or other users in your organization can use as a starting point for a new report's layout, data model, and queries. Templates in Power BI Desktop help you jump-start and standardize report creation.

Box 1: FLOAT

Identify which customers should receive promotional emails based on their likelihood of purchasing promoted products.

FLOT is used in the last statement of the code: WITH (score FLOAT) as p;

From syntax: MODEL

The MODEL parameter is used to specify the model used for scoring or prediction. The model is specified as a variable or a literal or a scalar expression.

Box 2: dbo.CustomerWithProductScore

Identify which customers should receive promotional emails based on their likelihood of purchasing promoted products.

Only table CustomerWithProductScore has the required filed score.

From the syntax:

DATA

The DATA parameter is used to specify the data used for scoring or prediction. Data is specified in the form of a table source in the query. Table source can be a table, table alias, CTE alias, view, or table-valued function.

A Synapse Analytics dedicated SQL pool is named SQLDW.

Customer contact data in SQLDW and the Power BI dataset must be labeled as Sensitive. Records must be kept of any users that use the sensitive data.

A (not B): Enable sensitivity labels

Sensitivity labels must be enabled on the tenant before they can be used in both the service and in Desktop.

To enable sensitivity labels on the tenant, go to the Power BI Admin portal, open the Tenant settings pane, and find the Information protection section.

In the Information Protection section, perform the following steps:

• Open Allow users to apply sensitivity labels for Power BI content.

• Enable the toggle.

D (not C): When data protection is enabled on your tenant, sensitivity labels appear in the sensitivity column in the list view of dashboards, reports, datasets, and dataflows.

E: Power BI Tenant Discovery Setting include Make certified content discoverable.

Step 1: From powerbi.com, create a new report..

The company wants custom Power BI usage reporting that includes the percent change of users that view reports in the Sales Analytics workspace each month.

Step 2: Add a report measure

Measures are used in some of the most common data analyses. Simple summarizations such as sums, averages, minimum, maximum and counts can be set through the Fields well. The calculated results of measures are always changing in response to your interaction with your reports, allowing for fast and dynamic ad-hoc data exploration.

Step 3: Add visuals to the report

Step 4: Publish the report to the Sales Analytics workspace

Development Process Requirements

Litware identifies the following development process requirements:

SQLDW and datalake1 will act as the development environment. Once feature development is complete, all entities in synapseworkspace1 will be promoted to a test workspace, and then to a production workspace.

Power BI content must be deployed to test and production by using deployment pipelines.

Create deployment rules

When working in a deployment pipeline, different stages may have different configurations. For example, each stage can have different databases or different query parameters. The development stage might query sample data from the database, while the test and production stages query the entire database.

When you deploy content between pipeline stages, configuring deployment rules enables you to allow changes to content, while keeping some settings intact. For example, if you want a dataset in a production stage to point to a production database, you can define a rule for this. The rule is defined in the production stage, under the appropriate dataset. Once the rule is defined, content deployed from test to production, will inherit the value as defined in the deployment rule, and will always apply as long as the rule is unchanged and valid.

You can configure data source rules and parameter rules.

Incorrect:

Not B: if you already have a steady production environment, you can deploy it backward (to Test or Dev, based on your need) and set up the pipeline. The feature is not limited to any sequential orders.

The sales data in SQLDW is updated every 30 minutes. Records in dbo.SalesTransactions are updated in SQLDW up to three days after being created. The records do NOT change after three days.