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DP-200 Practice Exam Free

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  • DP-200 Practice Exam Free – 50 Questions to Simulate the Real Exam
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DP-200 Practice Exam Free – 50 Questions to Simulate the Real Exam

Are you getting ready for the DP-200 certification? Take your preparation to the next level with our DP-200 Practice Exam Free – a carefully designed set of 50 realistic exam-style questions to help you evaluate your knowledge and boost your confidence.

Using a DP-200 practice exam free is one of the best ways to:

  • Experience the format and difficulty of the real exam
  • Identify your strengths and focus on weak areas
  • Improve your test-taking speed and accuracy

Below, you will find 50 realistic DP-200 practice exam free questions covering key exam topics. Each question reflects the structure and challenge of the actual exam.

Question 1

You have to deploy resources on Azure HDInsight for a batch processing job. The batch processing must run daily and must scale to minimize costs. You also be able to monitor cluster performance.
You need to decide on a tool that will monitor the clusters and provide information on suggestions on how to scale.
You decide on monitoring the cluster load by using the Ambari Web UI.
Would this fulfill the requirement?

A. Yes

B. No

 


Suggested Answer: A

Yes, this will give you a good idea on the load on the Azure HDInsight cluster.
The Microsoft documentation mentions the following:
Monitor cluster load –
Hadoop clusters can deliver the most optimal performance when the load on cluster is evenly distributed across all the nodes. This enables the processing tasks to run without being constrained by RAM, CPU, or disk resources on individual nodes.
To get a high-level look at the nodes of your cluster and their loading, sign in to the Ambari Web UI, then select the Hosts tab. Your hosts are listed by their fully qualified domain names. Each host’s operating status is shown by a colored health indicator:
Reference Image
Reference: alt=”Reference Image” />
Reference:
https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-key-scenarios-to-monitor

Question 2

You have an Azure subscription the contains the resources shown in the following table:
 Image
All the resources have the default encryption settings.
You need to ensure that all the data stored in the resources is encrypted at rest.
What should you do?

A. Enable Azure Storage encryption for storageaccount1.

B. Enable Transparent Data Encryption (TDE) for synapsedb1.

C. Enable Azure Storage encryption for storageaccount2.

D. Enable encryption at rest for cosmosdb1.

 


Suggested Answer: B

Incorrect answers:
A, C: Azure Disks, and data in Azure Storage accounts are automatically encrypted at rest by default
D: All user data stored in Azure Cosmos DB is encrypted at rest by default
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/transparent-data-encryption-byok-overview
https://docs.microsoft.com/en-us/azure/synapse-analytics/security/workspaces-encryption
https://docs.microsoft.com/en-us/azure/cosmos-db/database-encryption-at-rest

Question 3

You have an Azure subscription that contains an Azure Data Factory version 2 (V2) data factory named df1. Df1 contains a linked service.
You have an Azure Key vault named vault1 that contains an encryption key named key1.
You need to encrypt df1 by using key1.
What should you do first?

A. Disable purge protection on vault1.

B. Create a self-hosted integration runtime.

C. Disable soft delete on vault1.

D. Remove the linked service from df1.

 


Suggested Answer: D

Linked services are much like connection strings, which define the connection information needed for Data Factory to connect to external resources.
Incorrect Answers:
A, C: Data Factory requires two properties to be set on the Key Vault, Soft Delete and Do Not Purge
B: A self-hosted integration runtime copies data between an on-premises store and cloud storage.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/enable-customer-managed-key
https://docs.microsoft.com/en-us/azure/data-factory/concepts-linked-services
https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime

Question 4

You are developing a data engineering solution for a company. The solution will store a large set of key-value pair data by using Microsoft Azure Cosmos DB.
The solution has the following requirements:
✑ Data must be partitioned into multiple containers.
✑ Data containers must be configured separately.
✑ Data must be accessible from applications hosted around the world.
✑ The solution must minimize latency.
You need to provision Azure Cosmos DB.
Which three actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Configure account-level throughput.

B. Provision an Azure Cosmos DB account with the Azure Table API. Enable geo-redundancy.

C. Configure table-level throughput.

D. Replicate the data globally by manually adding regions to the Azure Cosmos DB account.

E. Provision an Azure Cosmos DB account with the Azure Table API. Enable multi-region writes.

 


Suggested Answer: E

Scale read and write throughput globally. You can enable every region to be writable and elastically scale reads and writes all around the world. The throughput that your application configures on an Azure Cosmos database or a container is guaranteed to be delivered across all regions associated with your Azure Cosmos account. The provisioned throughput is guaranteed up by financially backed SLAs.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/distribute-data-globally

Question 5

An application will use Microsoft Azure Cosmos DB as its data solution. The application will use the Cassandra API to support a column-based database type that uses containers to store items.
You need to provision Azure Cosmos DB. Which container name and item name should you use?  Each correct answer presents part of the solutions.
NOTE: Each correct answer selection is worth one point.

A. collection

B. rows

C. graph

D. entities

E. table

 


Suggested Answer: BE

B: Depending on the choice of the API, an Azure Cosmos item can represent either a document in a collection, a row in a table or a node/edge in a graph. The following table shows the mapping between API-specific entities to an Azure Cosmos item:
Reference Image
E: An Azure Cosmos container is specialized into API-specific entities as follows:
Reference Image
References: alt=”Reference Image” />
E: An Azure Cosmos container is specialized into API-specific entities as follows:
<img src=”https://www.examtopics.com/assets/media/exam-media/03872/0000800002.png” alt=”Reference Image” />
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/databases-containers-items

Question 6

You have an Azure SQL database that has masked columns.
You need to identify when a user attempts to infer data from the masked columns.
What should you use?

A. Azure Advanced Threat Protection (ATP)

B. custom masking rules

C. Transparent Data Encryption (TDE)

D. auditing

 


Suggested Answer: D

Dynamic Data Masking is designed to simplify application development by limiting data exposure in a set of pre-defined queries used by the application. While
Dynamic Data Masking can also be useful to prevent accidental exposure of sensitive data when accessing a production database directly, it is important to note that unprivileged users with ad-hoc query permissions can apply techniques to gain access to the actual data. If there is a need to grant such ad-hoc access,
Auditing should be used to monitor all database activity and mitigate this scenario.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking

Question 7

You plan to implement an Azure Cosmos DB database that will write 100,000,000 JSON records every 24 hours. The database will be replicated to three regions.
Only one region will be writable.
You need to select a consistency level for the database to meet the following requirements:
✑ Guarantee monotonic reads and writes within a session.
✑ Provide the fastest throughput.
✑ Provide the lowest latency.
Which consistency level should you select?

A. Strong

B. Bounded Staleness

C. Eventual

D. Session

E. Consistent Prefix

 


Suggested Answer: D

Session: Within a single client session reads are guaranteed to honor the consistent-prefix (assuming a single ג€writerג€ session), monotonic reads, monotonic writes, read-your-writes, and write-follows-reads guarantees. Clients outside of the session performing writes will see eventual consistency.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels

Question 8

You have a SQL pool in Azure Synapse.
A user reports that queries against the pool take longer than expected to complete.
You need to add monitoring to the underlying storage to help diagnose the issue.
Which two metrics should you monitor? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Cache used percentage

B. DWU Limit

C. Snapshot Storage Size

D. Active queries

E. Cache hit percentage

 


Suggested Answer: AE

A: Cache used is the sum of all bytes in the local SSD cache across all nodes and cache capacity is the sum of the storage capacity of the local SSD cache across all nodes.
E: Cache hits is the sum of all columnstore segments hits in the local SSD cache and cache miss is the columnstore segments misses in the local SSD cache summed across all nodes
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-concept-resource-utilization-query-activity

Question 9

DRAG DROP -
Your company plans to create an event processing engine to handle streaming data from Twitter.
The data engineering team uses Azure Event Hubs to ingest the streaming data.
You need to implement a solution that uses Azure Databricks to receive the streaming data from the Azure Event Hubs.
Which three actions should you recommend be performed in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
 Image

 


Suggested Answer:
Correct Answer Image

Step 1: Deploy the Azure Databricks service
Create an Azure Databricks workspace by setting up an Azure Databricks Service.
Step 2: Deploy a Spark cluster and then attach the required libraries to the cluster.
To create a Spark cluster in Databricks, in the Azure portal, go to the Databricks workspace that you created, and then select Launch Workspace.
Attach libraries to Spark cluster: you use the Twitter APIs to send tweets to Event Hubs. You also use the Apache Spark Event Hubs connector to read and write data into Azure Event Hubs. To use these APIs as part of your cluster, add them as libraries to Azure Databricks and associate them with your Spark cluster.
Step 3: Create and configure a Notebook that consumes the streaming data.
You create a notebook named ReadTweetsFromEventhub in Databricks workspace. ReadTweetsFromEventHub is a consumer notebook you use to read the tweets from Event Hubs.
References:
https://docs.microsoft.com/en-us/azure/azure-databricks/databricks-stream-from-eventhubs

Question 10

DRAG DROP -
You have an Azure Active Directory (Azure AD) tenant that contains a security group named Group1. You have an Azure Synapse Analytics dedicated SQL pool named dw1 that contains a schema named schema1.
You need to grant Group1 read-only permissions to all the tables and views in schema1. The solution must use the principle of least privilege.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Select and Place:
 Image

 


Suggested Answer:
Correct Answer Image

Step 1: Create a database role named Role1 and grant Role1 SELECT permissions to schema
You need to grant Group1 read-only permissions to all the tables and views in schema1.
Place one or more database users into a database role and then assign permissions to the database role.
Step 2: Assign Rol1 to the Group database user
Step 3: Assign the Azure role-based access control (Azure RBAC) Reader role for dw1 to Group1
Reference:
https://docs.microsoft.com/en-us/azure/data-share/how-to-share-from-sql

Question 11

You are developing a solution that will stream to Azure Stream Analytics. The solution will have both streaming data and reference data.
Which input type should you use for the reference data?

A. Azure Cosmos DB

B. Azure Event Hubs

C. Azure Blob storage

D. Azure IoT Hub

 


Suggested Answer: C

Stream Analytics supports Azure Blob storage and Azure SQL Database as the storage layer for Reference Data.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-use-reference-data

Question 12

HOTSPOT -
Which masking functions should you implement for each column to meet the data masking requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
 Image

 


Suggested Answer:
Correct Answer Image

Box 1: Custom text/string: A masking method, which exposes the first and/or last characters and adds a custom padding string in the middle.
Only show the last four digits of the values in a column named SuspensionSprings.
Box 2: Default –
Default uses a zero value for numeric data types (bigint, bit, decimal, int, money, numeric, smallint, smallmoney, tinyint, float, real).
Scenario: Only show a zero value for the values in a column named ShockOilWeight.
Scenario:
The company identifies the following data masking requirements for the Race Central data that will be stored in SQL Database:
✑ Only show a zero value for the values in a column named ShockOilWeight.
✑ Only show the last four digits of the values in a column named SuspensionSprings.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/dynamic-data-masking-overview

Question 13

DRAG DROP -
You are implementing an Azure Blob storage account for an application that has the following requirements:
✑ Data created during the last 12 months must be readily accessible.
✑ Blobs older than 24 months must use the lowest storage costs. This data will be accessed infrequently.
✑ Data created 12 to 24 months ago will be accessed infrequently but must be readily accessible at the lowest storage costs.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
 Image

 


Suggested Answer:
Correct Answer Image

Step 1: Create a block blob in a Blob storage account
First create the block blob.
Azure Blob storage lifecycle management offers a rich, rule-based policy for GPv2 and Blob storage accounts.
Step 2: Use an Azure Resource Manager template that has a lifecycle management policy
Step 3: Create a rule that has the rule actions of TierToCool and TierToArchive
Each rule definition includes a filter set and an action set. The filter set limits rule actions to a certain set of objects within a container or objects names.
Note: You can add a Rule through Azure portal:
Sign in to the Azure portal.
1. In the Azure portal, search for and select your storage account.
2. Under Blob service, select Lifecycle Management to view or change your rules.
3. Select the List View tab.
4. Select Add a rule and name your rule on the Details form. You can also set the Rule scope, Blob type, and Blob subtype values.
5. Select Base blobs to set the conditions for your rule. For example, blobs are moved to cool storage if they haven’t been modified for 30 days.
6. Etc.
Incorrect Answers:
✑ Schedule the lifecycle management policy to run:
You don’t Schedule the lifecycle management policy to run. The platform runs the lifecycle policy once a day. Once you configure a policy, it can take up to 24 hours for some actions to run for the first time.
✑ Create a rule filter:
No need for a rule filter. Rule filters limit rule actions to a subset of blobs within the storage account.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-lifecycle-management-concepts

Question 14

You have an alert on a SQL pool in Azure Synapse that uses the signal logic shown in the exhibit.
 Image
On the same day, failures occur at the following times:
✑ 08:01
✑ 08:03
✑ 08:04
✑ 08:06
✑ 08:11
✑ 08:16
✑ 08:19
The evaluation period starts on the hour.
At which times will alert notifications be sent?

A. 08:15 only

B. 08:10, 08:15, and 08:20

C. 08:05 and 08:10 only

D. 08:10 only

E. 08:05 only

 


Suggested Answer: B

Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/alerts-insights-configure-portal

Question 15

HOTSPOT -
You have an Azure Cosmos DB database.
You need to use Azure Stream Analytics to check for uneven distributions of queries that can affect performance.
Which two settings should you configure? To answer, select the appropriate settings in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
 Image

 


Suggested Answer:
Correct Answer Image

Box 1: RIGHT –
Use right for dates.
1- RIGHT means =
2- LEFT means .
Box 2: 20090101, 201001010, 20110101, 20120101
Four values are better than three or two.
Reference:
https://medium.com/@selcukkilinc23/what-it-means-range-right-and-left-in-table-partitioning-2d654cb99ade

Question 16

DRAG DROP -
You have an Azure Data Lake Storage Gen2 account that contains JSON files for customers. The files contain two attributes named FirstName and LastName.
You need to copy the data from the JSON files to an Azure Synapse Analytics table by using Azure Databricks. A new column must be created that concatenates the FirstName and LastName values.
You create the following components:
✑ A destination table in Azure Synapse
✑ An Azure Blob storage container
✑ A service principal
Which five actions should you perform in sequence next in a Databricks notebook? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
 Image

 


Suggested Answer:
Correct Answer Image

Step 1: Read the file into a data frame.
You can load the json files as a data frame in Azure Databricks.
Step 2: Perform transformations on the data frame.
Step 3:Specify a temporary folder to stage the data
Specify a temporary folder to use while moving data between Azure Databricks and Azure Synapse.
Step 4: Write the results to a table in Azure Synapse.
You upload the transformed data frame into Azure Synapse. You use the Azure Synapse connector for Azure Databricks to directly upload a dataframe as a table in a Azure Synapse.
Step 5: Drop the data frame –
Clean up resources. You can terminate the cluster. From the Azure Databricks workspace, select Clusters on the left. For the cluster to terminate, under Actions, point to the ellipsis (…) and select the Terminate icon.
Reference:
https://docs.microsoft.com/en-us/azure/azure-databricks/databricks-extract-load-sql-data-warehouse

Question 17

HOTSPOT -
Which masking functions should you implement for each column to meet the data masking requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
 Image

 


Suggested Answer:
Correct Answer Image

Box 1: Credit Card –
The Credit Card Masking method exposes the last four digits of the designated fields and adds a constant string as a prefix in the form of a credit card.
Example: XXXX-XXXX-XXXX-1234 –
✑ Only show the last four digits of the values in a column named SuspensionSprings.
Box 2: Default –
Default uses a zero value for numeric data types (bigint, bit, decimal, int, money, numeric, smallint, smallmoney, tinyint, float, real).
✑ Only show a zero value for the values in a column named ShockOilWeight.
Scenario:
The company identifies the following data masking requirements for the Race Central data that will be stored in SQL Database:
✑ Only show a zero value for the values in a column named ShockOilWeight.
✑ Only show the last four digits of the values in a column named SuspensionSprings.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/dynamic-data-masking-overview

Question 18

You have an Azure Storage account named storage1 that is configured as shown in the following exhibit.
 Image
You need to ensure that all calls to an Azure Storage REST API operation on storage1 are made over HTTPS.
What should you do?

A. Set Secure transfer required to Enabled.

B. Set Allow Blob public access to Disabled.

C. For the Blob service, create a shared access signature (SAS) that allows HTTPS only.

D. Set Minimum TLS version to Version 1.2.

 


Suggested Answer: A

You can configure your storage account to accept requests from secure connections only by setting the Secure transfer required property for the storage account.
When you require secure transfer, any requests originating from an insecure connection are rejected. Microsoft recommends that you always require secure transfer for all of your storage accounts.
When secure transfer is required, a call to an Azure Storage REST API operation must be made over HTTPS. Any request made over HTTP is rejected.
Reference:
https://docs.microsoft.com/en-us/azure/storage/common/storage-require-secure-transfer

Question 19

You need to deploy a Microsoft Azure Stream Analytics job for an IoT based solution. The solution must minimize latency. The solution must also minimize the bandwidth usage between the job and the IoT device.
Which of the following actions must you perform for this requirement? (Choose four.)

A. Ensure to configure routes

B. Create an Azure Blob storage container

C. Configure Streaming Units

D. Create an IoT Hub and add the Azure Stream Analytics modules to the IoT Hub namespace

E. Create an Azure Stream Analytics edge job and configure job definition save location

F. Create an Azure Stream Analytics cloud job and configure job definition save location

 


Suggested Answer: ABDF

There is an article in the Microsoft documentation on configuring Azure Stream Analytics on IoT Edge devices.
You need to have a storage container for the job definition:
Installation instructions –
The high-level steps are described in the following table. More details are given in the following sections.
Reference Image
You also need to create a cloud part job definition:
Reference Image
You also need to set the modules for your IoT edge device:
Deployment ASA on your IoT Edge device(s)
Add ASA to your deployment –
ג€¢ In the Azure portal, open IoT Hub, navigate to IoT Edge and click on the device you want to target for this deployment.
ג€¢ Select Set modules, then select + Add and choose Azure Stream Analytics Module.
ג€¢ Select the subscription and the ASA Edge job that you created. Click Save.
Reference Image
You also need to configure the Routes:
Configure routes –
IoT Edge provides a way to declaratively route messages between modules, and between modules and IoT Hub. The full syntax is described here. Names of the inputs and outputs created in the ASA job can be used as endpoints for routing.
Since this is clear from the Microsoft documentation, all other options are incorrect.
Reference: alt=”Reference Image” />
You also need to create a cloud part job definition:
Reference Image
You also need to set the modules for your IoT edge device:
Deployment ASA on your IoT Edge device(s)
Add ASA to your deployment –
ג€¢ In the Azure portal, open IoT Hub, navigate to IoT Edge and click on the device you want to target for this deployment.
ג€¢ Select Set modules, then select + Add and choose Azure Stream Analytics Module.
ג€¢ Select the subscription and the ASA Edge job that you created. Click Save.
<img src=”https://www.examtopics.com/assets/media/exam-media/03872/0056000001.jpg” alt=”Reference Image” />
You also need to configure the Routes:
Configure routes –
IoT Edge provides a way to declaratively route messages between modules, and between modules and IoT Hub. The full syntax is described here. Names of the inputs and outputs created in the ASA job can be used as endpoints for routing.
Since this is clear from the Microsoft documentation, all other options are incorrect.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge

Question 20

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
✑ A workload for data engineers who will use Python and SQL
✑ A workload for jobs that will run notebooks that use Python, Scala, and SQL
✑ A workload that data scientists will use to perform ad hoc analysis in Scala and R
The enterprise architecture team at your company identifies the following standards for Databricks environments:
✑ The data engineers must share a cluster.
✑ The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
✑ All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databricks clusters for the workloads.
Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.
Does this meet the goal?

A. Yes

B. No

 


Suggested Answer: B

We would need a High Concurrency cluster for the jobs.
Note:
Standard clusters are recommended for a single user. Standard can run workloads developed in any language: Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
References:
https://docs.azuredatabricks.net/clusters/configure.html

Question 21

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
A company uses Azure Data Lake Gen 1 Storage to store big data related to consumer behavior.
You need to implement logging.
Solution: Use information stored in Azure Active Directory reports.
Does the solution meet the goal?

A. Yes

B. No

 


Suggested Answer: B

Instead configure Azure Data Lake Storage diagnostics to store logs and metrics in a storage account.
Note:
You can enable diagnostic logging for your Azure Data Lake Storage Gen1 accounts, blobs, files, queues and tables.
Diagnostic logs aren’t available for Data Lake Storage Gen2 accounts [as of August 2019].
References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-diagnostic-logs
https://github.com/MicrosoftDocs/azure-docs/issues/34286

Question 22

Which two metrics should you use to identify the appropriate RU/s for the telemetry data? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Number of requests

B. Number of requests exceeded capacity

C. End to end observed read latency at the 99 th percentile

D. Session consistency

E. Data + Index storage consumed

F. Avg Throughput/s

 


Suggested Answer: AE

Scenario: The telemetry data must be monitored for performance issues. You must adjust the Cosmos DB Request Units per second (RU/s) to maintain a performance SLA while minimizing the cost of the RU/s.
With Azure Cosmos DB, you pay for the throughput you provision and the storage you consume on an hourly basis.
While you estimate the number of RUs per second to provision, consider the following factors:
Item size: As the size of an item increases, the number of RUs consumed to read or write the item also increases.

Question 23

Note: This question is a part of series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You develop a data ingestion process that will import data to an enterprise data warehouse in Azure Synapse Analytics. The data to be ingested resides in parquet files stored in an Azure Data Lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Data Warehouse.
Solution:
1. Create an external data source pointing to the Azure storage account
2. Create a workload group using the Azure storage account name as the pool name
3. Load the data using the INSERT`¦SELECT statement
Does the solution meet the goal?

A. Yes

B. No

 


Suggested Answer: B

You need to create an external file format and external table using the external data source.
You then load the data using the CREATE TABLE AS SELECT statement.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure-data-lake-store

Question 24

DRAG DROP -
You have an Azure Stream Analytics job that is a Stream Analytics project solution in Microsoft Visual Studio. The job accepts data generated by IoT devices in the JSON format.
You need to modify the job to accept data generated by the IoT devices in the Protobuf format.
Which three actions should you perform from Visual Studio in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
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Suggested Answer:
Correct Answer Image

Step 1: Add an Azure Stream Analytics Custom Deserializer Project (.NET) project to the solution.
Create a custom deserializer –
1. Open Visual Studio and select File > New > Project. Search for Stream Analytics and select Azure Stream Analytics Custom Deserializer Project (.NET). Give the project a name, like Protobuf Deserializer.
Reference Image
2. In Solution Explorer, right-click your Protobuf Deserializer project and select Manage NuGet Packages from the menu. Then install the
Microsoft.Azure.StreamAnalytics and Google.Protobuf NuGet packages.
3. Add the MessageBodyProto class and the MessageBodyDeserializer class to your project.
4. Build the Protobuf Deserializer project.
Step 2: Add .NET deserializer code for Protobuf to the custom deserializer project
Azure Stream Analytics has built-in support for three data formats: JSON, CSV, and Avro. With custom .NET deserializers, you can read data from other formats such as Protocol Buffer, Bond and other user defined formats for both cloud and edge jobs.
Step 3: Add an Azure Stream Analytics Application project to the solution
Add an Azure Stream Analytics project
1. In Solution Explorer, right-click the Protobuf Deserializer solution and select Add > New Project. Under Azure Stream Analytics > Stream Analytics, choose
Azure Stream Analytics Application. Name it ProtobufCloudDeserializer and select OK.
2. Right-click References under the ProtobufCloudDeserializer Azure Stream Analytics project. Under Projects, add Protobuf Deserializer. It should be automatically populated for you.
Reference: alt=”Reference Image” />
2. In Solution Explorer, right-click your Protobuf Deserializer project and select Manage NuGet Packages from the menu. Then install the
Microsoft.Azure.StreamAnalytics and Google.Protobuf NuGet packages.
3. Add the MessageBodyProto class and the MessageBodyDeserializer class to your project.
4. Build the Protobuf Deserializer project.
Step 2: Add .NET deserializer code for Protobuf to the custom deserializer project
Azure Stream Analytics has built-in support for three data formats: JSON, CSV, and Avro. With custom .NET deserializers, you can read data from other formats such as Protocol Buffer, Bond and other user defined formats for both cloud and edge jobs.
Step 3: Add an Azure Stream Analytics Application project to the solution
Add an Azure Stream Analytics project
1. In Solution Explorer, right-click the Protobuf Deserializer solution and select Add > New Project. Under Azure Stream Analytics > Stream Analytics, choose
Azure Stream Analytics Application. Name it ProtobufCloudDeserializer and select OK.
2. Right-click References under the ProtobufCloudDeserializer Azure Stream Analytics project. Under Projects, add Protobuf Deserializer. It should be automatically populated for you.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/custom-deserializer

Question 25

DRAG DROP -
You manage security for a database that supports a line of business application.
Private and personal data stored in the database must be protected and encrypted.
You need to configure the database to use Transparent Data Encryption (TDE).
Which five actions should you perform in sequence? To answer, select the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
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Suggested Answer:
Correct Answer Image

Step 1: Create a master key –
Step 2: Create or obtain a certificate protected by the master key
Step 3: Set the context to the company database
Step 4: Create a database encryption key and protect it by the certificate
Step 5: Set the database to use encryption
Example code:
USE master;
GO –
CREATE MASTER KEY ENCRYPTION BY PASSWORD = ”; go
CREATE CERTIFICATE MyServerCert WITH SUBJECT = ‘My DEK Certificate’; go
USE AdventureWorks2012;
GO –
CREATE DATABASE ENCRYPTION KEY –
WITH ALGORITHM = AES_128 –
ENCRYPTION BY SERVER CERTIFICATE MyServerCert;
GO –
ALTER DATABASE AdventureWorks2012
SET ENCRYPTION ON;
GO –
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/transparent-data-encryption

Question 26

Note: This question is a part of series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You develop a data ingestion process that will import data to an enterprise data warehouse in Azure Synapse Analytics. The data to be ingested resides in parquet files stored in an Azure Data Lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Data Warehouse.
Solution:
1. Use Azure Data Factory to convert the parquet files to CSV files
2. Create an external data source pointing to the Azure Data Lake Gen 2 storage account
3. Create an external file format and external table using the external data source
4. Load the data using the CREATE TABLE AS SELECT statement
Does the solution meet the goal?

A. Yes

B. No

 


Suggested Answer: A

It is not necessary to convert the parquet files to CSV files.
You need to create an external file format and external table using the external data source.
You load the data using the CREATE TABLE AS SELECT statement.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure-data-lake-store

Question 27

You create an Azure Databricks cluster and specify an additional library to install.
When you attempt to load the library to a notebook, the library is not found.
You need to identify the cause of the issue.
What should you review?

A. workspace logs

B. notebook logs

C. global init scripts logs

D. cluster event logs

 


Suggested Answer: C

Cluster-scoped Init Scripts: Init scripts are shell scripts that run during the startup of each cluster node before the Spark driver or worker JVM starts. Databricks customers use init scripts for various purposes such as installing custom libraries, launching background processes, or applying enterprise security policies.
Logs for Cluster-scoped init scripts are now more consistent with Cluster Log Delivery and can be found in the same root folder as driver and executor logs for the cluster.
Reference:
https://databricks.com/blog/2018/08/30/introducing-cluster-scoped-init-scripts.html

Question 28

HOTSPOT -
You are designing a new Lambda architecture on Microsoft Azure.
The real-time processing layer must meet the following requirements:
Ingestion:
✑ Receive millions of events per second
✑ Act as a fully managed Platform-as-a-Service (PaaS) solution
✑ Integrate with Azure Functions
Stream processing:
✑ Process on a per-job basis
✑ Provide seamless connectivity with Azure services
✑ Use a SQL-based query language
Analytical data store:
✑ Act as a managed service
✑ Use a document store
✑ Provide data encryption at rest
You need to identify the correct technologies to build the Lambda architecture using minimal effort. Which technologies should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
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Suggested Answer:
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Box 1: Azure Event Hubs –
This portion of a streaming architecture is often referred to as stream buffering. Options include Azure Event Hubs, Azure IoT Hub, and Kafka.
Incorrect Answers: Not HDInsight Kafka
Azure Functions need a trigger defined in order to run. There is a limited set of supported trigger types, and Kafka is not one of them.
Box 2: Azure Stream Analytics –
Azure Stream Analytics provides a managed stream processing service based on perpetually running SQL queries that operate on unbounded streams.
You can also use open source Apache streaming technologies like Storm and Spark Streaming in an HDInsight cluster.
Box 3: Azure Synapse Analytics –
Azure Synapse Analytics provides a managed service for large-scale, cloud-based data warehousing. HDInsight supports Interactive Hive, HBase, and Spark
SQL, which can also be used to serve data for analysis.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/

Question 29

HOTSPOT -
You have an Azure data factory that has two pipelines named PipelineA and PipelineB.
PipelineA has four activities as shown in the following exhibit.
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PipelineB has two activities as shown in the following exhibit.
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You create an alert for the data factory that uses Failed pipeline runs metrics for both pipelines and all failure types. The metric has the following settings:
✑ Operator: Greater than
✑ Aggregation type: Total
✑ Threshold value: 2
✑ Aggregation granularity (Period): 5 minutes
✑ Frequency of evaluation: Every 5 minutes
Data Factory monitoring records the failures shown in the following table.
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For each of the following statements, select yes if the statement is true. Otherwise, select no.
NOTE: Each correct answer selection is worth one point.
Hot Area:
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Suggested Answer:
Correct Answer Image

Box 1: No –
Only one failure at this point.
Box 2: No –
Only two failures within 5 minutes.
Box 3: Yes –
More than two (three) failures in 5 minutes
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/alerts-insights-configure-portal

Question 30

HOTSPOT -
A company plans to analyze a continuous flow of data from a social media platform by using Microsoft Azure Stream Analytics. The incoming data is formatted as one record per row.
You need to create the input stream.
How should you complete the REST API segment? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
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Suggested Answer:
Correct Answer Image

Box 1: CSV –
A comma-separated values (CSV) file is a delimited text file that uses a comma to separate values. A CSV file stores tabular data (numbers and text) in plain text.
Each line of the file is a data record.
JSON and AVRO are not formatted as one record per row.
Box 2: “type”:”Microsoft.ServiceBus/EventHub”,
Properties include “EventHubName”
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-inputs
https://en.wikipedia.org/wiki/Comma-separated_values

Question 31

HOTSPOT -
A company is deploying a service-based data environment. You are developing a solution to process this data.
The solution must meet the following requirements:
✑ Use an Azure HDInsight cluster for data ingestion from a relational database in a different cloud service
✑ Use an Azure Data Lake Storage account to store processed data
✑ Allow users to download processed data
You need to recommend technologies for the solution.
Which technologies should you use? To answer, select the appropriate options in the answer area.
Hot Area:
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Suggested Answer:
Correct Answer Image

Box 1: Apache Sqoop –
Apache Sqoop is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
Azure HDInsight is a cloud distribution of the Hadoop components from the Hortonworks Data Platform (HDP).
Incorrect Answers:
DistCp (distributed copy) is a tool used for large inter/intra-cluster copying. It uses MapReduce to effect its distribution, error handling and recovery, and reporting.
It expands a list of files and directories into input to map tasks, each of which will copy a partition of the files specified in the source list. Its MapReduce pedigree has endowed it with some quirks in both its semantics and execution.
RevoScaleR is a collection of proprietary functions in Machine Learning Server used for practicing data science at scale. For data scientists, RevoScaleR gives you data-related functions for import, transformation and manipulation, summarization, visualization, and analysis.
Box 2: Apache Kafka –
Apache Kafka is a distributed streaming platform.
A streaming platform has three key capabilities:
Publish and subscribe to streams of records, similar to a message queue or enterprise messaging system.
Store streams of records in a fault-tolerant durable way.
Process streams of records as they occur.
Kafka is generally used for two broad classes of applications:
Building real-time streaming data pipelines that reliably get data between systems or applications
Building real-time streaming applications that transform or react to the streams of data
Box 3: Ambari Hive View –
You can run Hive queries by using Apache Ambari Hive View. The Hive View allows you to author, optimize, and run Hive queries from your web browser.
References:
https://sqoop.apache.org/

https://kafka.apache.org/intro

https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-use-hive-ambari-view

Question 32

You are creating a new notebook in Azure Databricks that will support R as the primary language but will also support Scala and SQL.
Which switch should you use to switch between languages?

A. %

B. []

C. ()

D. @

 


Suggested Answer: A

You can override the primary language by specifying the language magic command % at the beginning of a cell. The supported magic commands are:
%python, %r, %scala, and %sql.
References:
https://docs.databricks.com/user-guide/notebooks/notebook-use.html#mix-languages

Question 33

HOTSPOT -
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at rest layer must meet the following requirements:
Data storage:
✑ Serve as a repository for high volumes of large files in various formats.
✑ Implement optimized storage for big data analytics workloads.
✑ Ensure that data can be organized using a hierarchical structure.
Batch processing:
✑ Use a managed solution for in-memory computation processing.
✑ Natively support Scala, Python, and R programming languages.
✑ Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
✑ Support parallel processing.
✑ Use columnar storage.
✑ Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
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Suggested Answer:
Correct Answer Image

Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP,
MapReduce.
Languages: R, Python, Java, Scala, SQL
Analytic data store: Azure Synapse Analytics
Azure Synapse Analytics Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
Azure Synapse Analytics stores data into relational tables with columnar storage.
Note: As of November 2019, Azure SQL Data Warehouse is now Azure Synapse Analytics.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is

Question 34

HOTSPOT -
You have a SQL pool in Azure Synapse.
You plan to load data from Azure Blob storage to a staging table. Approximately 1 million rows of data will be loaded daily. The table will be truncated before each daily load.
You need to create the staging table. The solution must minimize how long it takes to load the data to the staging table.
How should you configure the table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
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Suggested Answer:
Correct Answer Image

Box 1: Hash –
Hash-distributed tables improve query performance on large fact tables. hey can have very large numbers of rows and still achieve high performance.
Incorrect:
Round-robin tables are useful for improving loading speed.
Box 2: Clustered columnstore –
When creating partitions on clustered columnstore tables, it is important to consider how many rows belong to each partition. For optimal compression and performance of clustered columnstore tables, a minimum of 1 million rows per distribution and partition is needed.
Box 3: Date –
Table partitions enable you to divide your data into smaller groups of data. In most cases, table partitions are created on a date column.
Partition switching can be used to quickly remove or replace a section of a table.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-partition
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-distribute

Question 35

DRAG DROP -
You plan to create a new single database instance of Microsoft Azure SQL Database.
The database must only allow communication from the data engineer's workstation. You must connect directly to the instance by using Microsoft SQL Server
Management Studio.
You need to create and configure the Database. Which three Azure PowerShell cmdlets should you use to develop the solution? To answer, move the appropriate cmdlets from the list of cmdlets to the answer area and arrange them in the correct order.
Select and Place:
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Suggested Answer:
Correct Answer Image

Step 1: New-AzureSqlServer –
Create a server.
Step 2: New-AzureRmSqlServerFirewallRule
New-AzureRmSqlServerFirewallRule creates a firewall rule for a SQL Database server.
Can be used to create a server firewall rule that allows access from the specified IP range.
Step 3: New-AzureRmSqlDatabase –
Example: Create a database on a specified server
PS C:>New-AzureRmSqlDatabase -ResourceGroupName “ResourceGroup01” -ServerName “Server01” -DatabaseName “Database01
References:
https://docs.microsoft.com/en-us/azure/sql-database/scripts/sql-database-create-and-configure-database-powershell?toc=%2fpowershell%2fmodule%2ftoc.json

Question 36

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
A company uses Azure Data Lake Gen 1 Storage to store big data related to consumer behavior.
You need to implement logging.
Solution: Configure Azure Data Lake Storage diagnostics to store logs and metrics in a storage account.
Does the solution meet the goal?

A. Yes

B. No

 


Suggested Answer: A

From the Azure Storage account that contains log data, open the Azure Storage account blade associated with Data Lake Storage Gen1 for logging, and then click Blobs. The Blob service blade lists two containers.
Reference Image
Note:
You can enable diagnostic logging for your Azure Data Lake Storage Gen1 accounts, blobs, files, queues and tables.
Diagnostic logs aren’t available for Data Lake Storage Gen2 accounts [as of August 2019].
Reference: alt=”Reference Image” />
Note:
You can enable diagnostic logging for your Azure Data Lake Storage Gen1 accounts, blobs, files, queues and tables.
Diagnostic logs aren’t available for Data Lake Storage Gen2 accounts [as of August 2019].
Reference:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-diagnostic-logs
https://github.com/MicrosoftDocs/azure-docs/issues/34286

Question 37

You need to implement event processing by using Stream Analytics to produce consistent JSON documents.
Which three actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Define an output to Cosmos DB.

B. Define a query that contains a JavaScript user-defined aggregates (UDA) function.

C. Define a reference input.

D. Define a transformation query.

E. Define an output to Azure Data Lake Storage Gen2.

F. Define a stream input.

 


Suggested Answer: DEF

✑ DOCDB stored documents that connect to the sales data in SALESDB. The documents are stored in two different JSON formats based on the sales channel.
✑ The sales data, including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytic process will perform aggregations that must be done continuously, without gaps, and without overlapping.
As they arrive, all the sales documents in JSON format must be transformed into one consistent format.
<img src=”https://www.examtopics.com/assets/media/exam-media/03872/0014200003.png” alt=”Reference Image” />

Question 38

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
A company uses Azure Data Lake Gen 1 Storage to store big data related to consumer behavior.
You need to implement logging.
Solution: Create an Azure Automation runbook to copy events.
Does the solution meet the goal?

A. Yes

B. No

 


Suggested Answer: B

Instead configure Azure Data Lake Storage diagnostics to store logs and metrics in a storage account.
Note:
You can enable diagnostic logging for your Azure Data Lake Storage Gen1 accounts, blobs, files, queues and tables.
Diagnostic logs aren’t available for Data Lake Storage Gen2 accounts [as of August 2019].
Reference:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-diagnostic-logs
https://github.com/MicrosoftDocs/azure-docs/issues/34286

Question 39

DRAG DROP -
You develop data engineering solutions for a company.
A project requires analysis of real-time Twitter feeds. Posts that contain specific keywords must be stored and processed on Microsoft Azure and then displayed by using Microsoft Power BI. You need to implement the solution.
Which five actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
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Suggested Answer:
Correct Answer Image

Step 1: Create an HDInisght cluster with the Spark cluster type
Step 2: Create a Jyputer Notebook
Step 3: Create a table –
The Jupyter Notebook that you created in the previous step includes code to create an hvac table.
Step 4: Run a job that uses the Spark Streaming API to ingest data from Twitter
Step 5: Load the hvac table into Power BI Desktop
You use Power BI to create visualizations, reports, and dashboards from the Spark cluster data.
References:
https://acadgild.com/blog/streaming-twitter-data-using-spark

https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-use-with-data-lake-store

Question 40

Your company uses Azure Stream Analytics to monitor devices.
The company plans to double the number of devices that are monitored.
You need to monitor a Stream Analytics job to ensure that there are enough processing resources to handle the additional load.
Which metric should you monitor?

A. Input Deserialization Errors

B. Early Input Events

C. Late Input Events

D. Watermark delay

 


Suggested Answer: D

There are a number of other resource constraints that can cause the streaming pipeline to slow down. The watermark delay metric can rise due to:
✑ Not enough processing resources in Stream Analytics to handle the volume of input events.
✑ Not enough throughput within the input event brokers, so they are throttled.
✑ Output sinks are not provisioned with enough capacity, so they are throttled. The possible solutions vary widely based on the flavor of output service being used.
Incorrect Answers:
A: Deserialization issues are caused when the input stream of your Stream Analytics job contains malformed messages.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-time-handling

Question 41

You need to implement complex stateful business logic within an Azure Stream Analytics service.
Which type of function should you create in the Stream Analytics topology?

A. JavaScript user-define functions (UDFs)

B. Azure Machine Learning

C. JavaScript user-defined aggregates (UDA)

 


Suggested Answer: C

Azure Stream Analytics supports user-defined aggregates (UDA) written in JavaScript, it enables you to implement complex stateful business logic. Within UDA you have full control of the state data structure, state accumulation, state decumulation, and aggregate result computation.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-javascript-user-defined-aggregates

Question 42

You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data solution to collect, process, and maintain data.
The analytical data store performs poorly.
You must implement a solution that meets the following requirements:
✑ Provide data warehousing
✑ Reduce ongoing management activities
✑ Deliver SQL query responses in less than one second
You need to create an HDInsight cluster to meet the requirements.
Which type of cluster should you create?

A. Interactive Query

B. Apache Hadoop

C. Apache HBase

D. Apache Spark

 


Suggested Answer: D

Lambda Architecture with Azure:
Azure offers you a combination of following technologies to accelerate real-time big data analytics:
1. Azure Cosmos DB, a globally distributed and multi-model database service.
2. Apache Spark for Azure HDInsight, a processing framework that runs large-scale data analytics applications.
3. Azure Cosmos DB change feed, which streams new data to the batch layer for HDInsight to process.
4. The Spark to Azure Cosmos DB Connector
Reference Image
Note: Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch processing and stream processing methods, and minimizing the latency involved in querying big data.
References: alt=”Reference Image” />
Note: Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch processing and stream processing methods, and minimizing the latency involved in querying big data.
References:
https://sqlwithmanoj.com/2018/02/16/what-is-lambda-architecture-and-what-azure-offers-with-its-new-cosmos-db/

Question 43

You have an Azure Stream Analytics job.
You need to ensure that the job has enough streaming units provisioned.
You configure monitoring of the SU% Utilization metric.
Which two additional metrics should you monitor? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Watermark Delay

B. Late Input Events

C. Out of order Events

D. Backlogged Input Events

E. Function Events

 


Suggested Answer: BD

B: Late Input Events: events that arrived later than the configured late arrival tolerance window.
Note: While comparing utilization over a period of time, use event rate metrics. InputEvents and OutputEvents metrics show how many events were read and processed.
D: In job diagram, there is a per partition backlog event metric for each input. If the backlog event metric keeps increasing, it’s also an indicator that the system resource is constrained (either because of output sink throttling, or high CPU).
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-scale-jobs

Question 44

You have an Azure Blob storage account.
The storage account has an alert that is configured to indicate when the Availability metric falls below 100 percent.
You receive an alert for the Availability metric. The logs for the storage account show that requests are failing because of a ServerTimeoutError error.
What does ServerTimeoutError indicate?

A. Read and write storage requests exceeded capacity.

B. A transient server timeout occurred while the service was moved to a different partition to load balance requests.

C. A client application attempted to perform an operation and did not have valid credentials.

D. There was excessive network latency between a client application and the storage account.

 


Suggested Answer: D

 

Question 45

HOTSPOT -
You need to build a solution to collect the telemetry data for Race Central.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
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Suggested Answer:
Correct Answer Image

API: Table –
Azure Cosmos DB provides native support for wire protocol-compatible APIs for popular databases. These include MongoDB, Apache Cassandra, Gremlin, and
Azure Table storage.
Scenario: The telemetry data must migrate toward a solution that is native to Azure.
Consistency level: Strong –
Use the strongest consistency Strong to minimize convergence time.
Scenario: The data must be written to the Azure datacenter closest to each race and must converge in the least amount of time.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels

Question 46

DRAG DROP -
You have an Azure Synapse Analytics SQL pool named Pool1 on a logical Microsoft SQL server named Server1.
You need to implement Transparent Data Encryption (TDE) on Pool1 by using a custom key named key1.
Which five actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
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Suggested Answer:
Correct Answer Image

Step 1: Assign a managed identity to Server1
You will need an existing Managed Instance as a prerequisite.
Step 2: Create an Azure key vault and grant the managed identity permissions to the vault
Create Resource and setup Azure Key Vault.
Step 3 :Add key1 to the Azure key vault
The recommended way is to import an existing key from a .pfx file or get an existing key from the vault. Alternatively, generate a new key directly in Azure Key
Vault.
Step 4: Configure key1 as the TDE protector for Server1
Provide TDE Protector key –
Step 5: Enable TDE on Pool1 –
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/managed-instance/scripts/transparent-data-encryption-byok-powershell

Question 47

HOTSPOT -
You are implementing automatic tuning mode for Azure SQL databases.
Automatic tuning mode is configured as shown in the following table.
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For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:
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Suggested Answer:
Correct Answer Image

Automatic tuning options can be independently enabled or disabled per database, or they can be configured on SQL Database servers and applied on every database that inherits settings from the server. SQL Database servers can inherit Azure defaults for Automatic tuning settings. Azure defaults at this time are set to FORCE_LAST_GOOD_PLAN is enabled, CREATE_INDEX is enabled, and DROP_INDEX is disabled.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-automatic-tuning

Question 48

DRAG DROP -
Your company has an on-premises Microsoft SQL Server instance.
The data engineering team plans to implement a process that copies data from the SQL Server instance to Azure Blob storage once a day. The process must orchestrate and manage the data lifecycle.
You need to create Azure Data Factory to connect to the SQL Server instance.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
 Image

 


Suggested Answer:
Correct Answer Image

Step 1: Create an Azure Data Factory
You need to create a data factory and start the Data Factory UI to create a pipeline in the data factory.
Step 2: From the on-premises network, install and configure a self-hosted runtime.
To use copy data from a SQL Server database that isn’t publicly accessible, you need to set up a self-hosted integration runtime.
Step 3: Configure a linked service to connect to the SQL Server instance.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/connector-sql-server
https://www.mssqltips.com/sqlservertip/5812/connect-to-onpremises-data-in-azure-data-factory-with-the-selfhosted-integration-runtime–part-1/

Question 49

DRAG DROP -
You develop data engineering solutions for a company. You must migrate data from Microsoft Azure Blob storage to an Azure SQL Data Warehouse for further transformation. You need to implement the solution.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
 Image

 


Suggested Answer:
Correct Answer Image

Step 1: Provision an Azure SQL Data Warehouse instance.
Create a data warehouse in the Azure portal.
Step 2: Connect to the Azure SQL Data warehouse by using SQL Server Management Studio
Connect to the data warehouse with SSMS (SQL Server Management Studio)
Step 3: Build external tables by using the SQL Server Management Studio
Create external tables for data in Azure blob storage.
You are ready to begin the process of loading data into your new data warehouse. You use external tables to load data from the Azure storage blob.
Step 4: Run Transact-SQL statements to load data.
You can use the CREATE TABLE AS SELECT (CTAS) T-SQL statement to load the data from Azure Storage Blob into new tables in your data warehouse.
References:
https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/sql-data-warehouse/load-data-from-azure-blob-storage-using-polybase.md

Question 50

You need to develop a pipeline for processing data. The pipeline must meet the following requirements:
✑ Scale up and down resources for cost reduction
✑ Use an in-memory data processing engine to speed up ETL and machine learning operations.
✑ Use streaming capabilities
✑ Provide the ability to code in SQL, Python, Scala, and R
Integrate workspace collaboration with Git
 Image
What should you use?

A. HDInsight Spark Cluster

B. Azure Stream Analytics

C. HDInsight Hadoop Cluster

D. Azure SQL Data Warehouse

E. HDInsight Kafka Cluster

F. HDInsight Storm Cluster

 


Suggested Answer: A

Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP,
MapReduce.
Languages: R, Python, Java, Scala, SQL
You can create an HDInsight Spark cluster using an Azure Resource Manager template. The template can be found in GitHub.
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing

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