A company has a real-time data analysis solution that is hosted on Microsoft Azure. The solution uses Azure Event Hub to ingest data and an Azure Stream Analytics cloud job to analyze the data. The cloud job is configured to use 120 Streaming Units (SU).You need to optimize performance for the Azure Stream Analytics job. Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

Scale the SU count for the job up.

Implement query parallelization by partitioning the data input.

Implement Azure Stream Analytics user-defined functions (UDF).

Implement query parallelization by partitioning the data output.

Scale the SU count for the job up.

Scale the SU count for the job down.

Implement query parallelization by partitioning the data input.

You have an Azure Data Factory instance that contains two pipelines named Pipeline1 and Pipeline2.Pipeline1 has the activities shown in the following exhibit. Pipeline2 has the activities shown in the following exhibit. You execute Pipeline2, and Stored procedure1 in Pipeline1 fails.What is the status of the pipeline runs?

Pipeline1 and Pipeline2 succeeded.

Pipeline1 and Pipeline2 failed.

Pipeline1 succeeded and Pipeline2 failed.

Pipeline1 failed and Pipeline2 succeeded.

You need to implement a Type 3 slowly changing dimension (SCD) for product category data in an Azure Synapse Analytics dedicated SQL pool.You have a table that was created by using the following Transact-SQL statement. Which two columns should you add to the table? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.

[CurrentProductCategory] [nvarchar] (100) NOT NULL,

[OriginalProductCategory] [nvarchar] (100) NOT NULL,

[EffectiveStartDate] [datetime] NOT NULL,

[CurrentProductCategory] [nvarchar] (100) NOT NULL,

[EffectiveEndDate] [datetime] NULL,

[ProductCategory] [nvarchar] (100) NOT NULL,

[OriginalProductCategory] [nvarchar] (100) NOT NULL,

You are creating an Azure Data Factory data flow that will ingest data from a CSV file, cast columns to specified types of data, and insert the data into a table in an Azure Synapse Analytic dedicated SQL pool. The CSV file contains three columns named username, comment, and date.The data flow already contains the following:A source transformation.A Derived Column transformation to set the appropriate types of data. A sink transformation to land the data in the pool. You need to ensure that the data flow meets the following requirements:All valid rows must be written to the destination table.Truncation errors in the comment column must be avoided proactively. Any rows containing comment values that will cause truncation errors upon insert must be written to a file in blob storage. Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

To the data flow, add a sink transformation to write the rows to a file in blob storage.

To the data flow, add a Conditional Split transformation to separate the rows that will cause truncation errors.

To the data flow, add a sink transformation to write the rows to a file in blob storage.

To the data flow, add a Conditional Split transformation to separate the rows that will cause truncation errors.

To the data flow, add a filter transformation to filter out rows that will cause truncation errors.

Add a select transformation to select only the rows that will cause truncation errors.

You have an Azure Storage account and a data warehouse in Azure Synapse Analytics in the UK South region. You need to copy blob data from the storage account to the data warehouse by using Azure Data Factory. The solution must meet the following requirements:Ensure that the data remains in the UK South region at all times. Minimize administrative effort. Which type of integration runtime should you use?

Self-hosted integration runtime

You have an Azure Stream Analytics job that receives clickstream data from an Azure event hub. You need to define a query in the Stream Analytics job. The query must meet the following requirements:Count the number of clicks within each 10-second window based on the country of a visitor. Ensure that each click is NOT counted more than once. How should you define the Query?

SELECT Country, Count(*) AS CountFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, TumblingWindow(second, 10)

SELECT Country, Avg(*) AS AverageFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, SlidingWindow(second, 10)

SELECT Country, Count(*) AS CountFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, TumblingWindow(second, 10)

SELECT Country, Avg(*) AS AverageFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, HoppingWindow(second, 10, 2)

SELECT Country, Count(*) AS CountFROM ClickStream TIMESTAMP BY CreatedAtGROUP BY Country, SessionWindow(second, 5, 10)

You have two Azure Data Factory instances named ADFdev and ADFprod. ADFdev connects to an Azure DevOps Git repository. You publish changes from the main branch of the Git repository to ADFdev. You need to deploy the artifacts from ADFdev to ADFprod.What should you do first?

From Azure DevOps, create a release pipeline.

From ADFdev, modify the Git configuration.

From ADFdev, create a linked service.

From Azure DevOps, create a release pipeline.

From Azure DevOps, update the main branch.

You are designing an Azure Databricks table. The table will ingest an average of 20 million streaming events per day. You need to persist the events in the table for use in incremental load pipeline jobs in Azure Databricks. The solution must minimize storage costs and incremental load times. What should you include in the solution?

Use a JSON format for physical data storage.

You have an Azure Databricks workspace named workspace1 in the Standard pricing tier. You need to configure workspace1 to support autoscaling all-purpose clusters. The solution must meet the following requirements:Automatically scale down workers when the cluster is underutilized for three minutes. Minimize the time it takes to scale to the maximum number of workers. Minimize costs. What should you do first?

Upgrade workspace1 to the Premium pricing tier.

Enable container services for workspace1.

Upgrade workspace1 to the Premium pricing tier.

Set Cluster Mode to High Concurrency.

Create a cluster policy in workspace1.

Microsoft DP-203 Practice Test 3 - Free Online Exam Questions 81-120

You are performing exploratory analysis of the bus fare data in an Azure Data Lake Storage Gen2 account by using an Azure Synapse Analytics serverless SQL pool.

You execute the Transact-SQL query shown in the following exhibit.

Microsoft DP-203 image Question 27 89500 10022024015849000000

What do the query results include?

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Microsoft DP-203 Practice Test 3

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