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2)- Updated DP-203 Dumps Practice Exam Questions Q1-Q15:

QUESTION 1 #

HOTSPOT
You are planning the deployment of Azure Data Lake Storage Gen2.
You have the following two reports that will access the data lake:

Report1: Reads three columns from a file that contains 50 columns.
Report2: Queries a single record based on a timestamp.
You need to recommend in which format to store the data in the data lake to support the reports. The solution must
minimize read times.

What should you recommend for each report? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Report1: CSV
CSV: The destination writes records as delimited data.
Report2: AVRO
AVRO supports timestamps.
Not Parquet, TSV: Not options for Azure Data Lake Storage Gen2.

Reference:
https://streamsets.com/documentation/datacollector/latest/help/datacollector/UserGuide/Destinations/ADLS-G2-D.html

QUESTION 2 #

DRAG-DROP
You need to ensure that the Twitter feed data can be analyzed in the dedicated SQL pool. The solution must meet the
customer sentiment analytic requirements.

Which three Transact-SQL DDL commands should you run in sequence? To answer, move the appropriate commands
from the list of commands 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.

Scenario: Allow Contoso users to use PolyBase in an Azure Synapse Analytics dedicated SQL pool to query the content
of the data records that host the Twitter feeds. Data must be protected by using row-level security (RLS). The users
must be authenticated by using their own Azure AD credentials.

Box 1: CREATE EXTERNAL DATA SOURCE
External data sources are used to connect to storage accounts.

Box 2: CREATE EXTERNAL FILE FORMAT CREATE EXTERNAL FILE FORMAT creates an external file format object that defines external data stored in Azure Blob Storage or Azure Data Lake Storage. Creating an external file format is a prerequisite for creating an external table.

Box 3: CREATE EXTERNAL TABLE AS SELECT

When used in conjunction with the CREATE TABLE AS SELECT statement, selecting from an external table imports
data into a table within the SQL pool. In addition to the COPY statement, external tables are useful for loading data.

Incorrect Answers:
CREATE EXTERNAL TABLE The CREATE EXTERNAL TABLE command creates an external table for Synapse SQL to access data stored in Azure Blob Storage or Azure Data Lake Storage.

Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-external-tables

QUESTION 3 #

You have an Azure Synapse Analytics dedicated SQL pool.
You need to ensure that data in the pool is encrypted at rest. The solution must NOT require modifying applications that query the data.
What should you do?

A. Enable encryption at rest for the Azure Data Lake Storage Gen2 account.
B. Enable Transparent Data Encryption (TDE) for the pool.
C. Use a customer-managed key to enable double encryption for the Azure Synapse workspace.
D. Create an Azure key vault in the Azure subscription to grant access to the pool.\

Correct Answer: B

Transparent Data Encryption (TDE) helps protect against the threat of malicious activity by encrypting and decrypting
your data at rest. When you encrypt your database, associated backups and transaction log files are encrypted without
requiring any changes to your applications.

TDE encrypts the storage of an entire database by using a symmetric key
called the database encryption key.

Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-overviewmanage-security

QUESTION 4 #

You have a table in an Azure Synapse Analytics dedicated SQL pool. The table was created by using the following
Transact-SQL statement.

You need to alter the table to meet the following requirements:
Ensure that users can identify the current manager of employees.
Support creating an employee reporting hierarchy for your entire company.
Provide fast lookup of the managers\’ attributes such as name and job title.

Which column should you add to the table?

A. [ManagerEmployeeID] [int] NULL
B. [ManagerEmployeeID] [smallint] NULL
C. [ManagerEmployeeKey] [int] NULL
D. [ManagerName] varchar NULL
Correct Answer: A

Use the same definition as the EmployeeID column.
Reference: https://docs.microsoft.com/en-us/analysis-services/tabular-models/hierarchies-ssas-tabular

QUESTION 5 #

HOTSPOT
You have an Azure event hub named retail hub that has 16 partitions. Transactions are posted to the retail hub. Each
transaction includes the transaction ID, the individual line items, and the payment details. The transaction ID is used as
the partition key.

You are designing an Azure Stream Analytics job to identify potentially fraudulent transactions at a
retail store. The job will use the retail hub as the input. The job will output the transaction ID, the individual line items, the payment details, a fraud score, and a fraud indicator.

You plan to send the output to an Azure event hub named fraud hub.
You need to ensure that the fraud detection solution is highly scalable and processes transactions as quickly as
possible.

How should you structure the output of the Stream Analytics job? To answer, select the appropriate options in the
answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Box 1: 16
For Event Hubs, you need to set the partition key explicitly.
An embarrassingly parallel job is the most scalable scenario in Azure Stream Analytics. It connects one partition of the
input to one instance of the query to one partition of the output.
Box 2: Transaction ID

Reference:
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-features#partitions

QUESTION 6 #

HOTSPOT
You have a self-hosted integration runtime in Azure Data Factory.
The current status of the integration runtime has the following configurations:

Status: Running Type: Self-Hosted Version: 4.4.7292.1 Running / Registered Node(s): 1/1 High Availability Enabled:
False Linked Count: 0 Queue Length: 0 Average Queue Duration. 0.00s
The integration runtime has the following node details:

Name: X-M Status: Running Version: 4.4.7292.1 Available Memory: 7697MB CPU Utilization: 6% Network (In/Out):
1.21KBps/0.83KBps Concurrent Jobs (Running/Limit): 2/14

Role: Dispatcher/Worker
Credential Status: In Sync
Use the drop-down menus to select the answer choice that completes each statement based on the information
presented.

NOTE: Each correct selection is worth one point.
Hot Area:

Correct Answer:

Box 1: fail until the node comes back online
We see: High Availability Enabled: False
Note Higher availability of the self-hosted integration runtime so that it\\’s no longer the single point of failure in your big data solution or cloud data integration with Data Factory.

Box 2: lowered
We see:
Concurrent Jobs (Running/Limit): 2/14
CPU Utilization: 6%
Note: When the processor and available RAM aren\\’t well utilized, but the execution of concurrent jobs reaches a
node\\’s limits, scale up by increasing the number of concurrent jobs that a node can run

Reference:
https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime

QUESTION 7 #

HOTSPOT
You have a data model that you plan to implement in a data warehouse in Azure Synapse Analytics as shown in the
the following exhibit.

All the dimension tables will be less than 2 GB after compression, and the fact table will be approximately 6 TB. Which
type of table should you use for each table? To answer, select the appropriate options in the answer area. NOTE: Each
correct selection is worth one point.

Hot Area:

Correct Answer:

QUESTION 8 #

You have a partitioned table in an Azure Synapse Analytics dedicated SQL pool. You need to design queries to
maximize the benefits of partition elimination. What should you include in the Transact-SQL queries?

A. JOIN
B. WHERE
C. DISTINCT
D. GROUP BY

Correct Answer: B

QUESTION 9 #

You need to schedule an Azure Data Factory pipeline to execute when a new file arrives in an Azure Data Lake Storage
Gen2 container.

Which type of trigger should you use?

A. on-demand
B. tumbling window
C. schedule
D. event

Correct Answer: D

Event-driven architecture (EDA) is a common data integration pattern that involves production, detection, consumption,
and reaction to events.

Data integration scenarios often require Data Factory customers to trigger pipelines based on
events happening in the storage account, such as the arrival or deletion of a file in the Azure Blob Storage account.

Reference: https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-event-trigger

QUESTION 10 #

You are designing an enterprise data warehouse in Azure Synapse Analytics that will contain a table named Customers.
Customers will contain credit card information.

You need to recommend a solution to provide salespeople with the ability to view all the entries in Customers. The
the solution must prevent all the salespeople from viewing or inferring the credit card information.

What should you include in the recommendation?

A. data masking
B. Always Encrypted
C. column-level security
D. row-level security

Correct Answer: A

SQL Database dynamic data masking limits sensitive data exposure by masking it to non-privileged users.
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

Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-dynamic-data-masking-get-started

QUESTION 11 #

HOTSPOT
You have an on-premises data warehouse that includes the following fact tables. Both tables have the following
columns: DateKey, ProductKey, RegionKey. There are 120 unique product keys and 65 unique region keys.

Queries that use the data warehouse take a long time to complete.
You plan to migrate the solution to use Azure Synapse Analytics. You need to ensure that the Azure-based solution
optimizes query performance and minimizes processing skew.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point
Hot Area:

Correct Answer:
QUESTION 12 #

You have an Azure Synapse workspace named MyWorkspace that contains an Apache Spark database named
mytestdb.

You run the following command in an Azure Synapse Analytics Spark pool in MyWorkspace.
CREATE TABLE mytestdb.myParquetTable( EmployeeID int, EmployeeName string, EmployeeStartDate date)
USING Parquet You then use Spark to insert a row into mytestdb. myParquetTable. The row contains the following data.

One minute later, you execute the following query from a serverless SQL pool in MyWorkspace.
SELECT EmployeeID FROM mytestdb.dbo.myParquetTable WHERE name = \\’Alice\\’;
What will be returned by the query?

A. 24
B. an error
C. a null value

Correct Answer: A

Once a database has been created by a Spark job, you can create tables in it with Spark that use Parquet as the
storage format. Table names will be converted to lower case and need to be queried using the lower case name.

These tables will immediately become available for querying by any of the Azure Synapse workspace Spark pools. They can also be used from any of the Spark jobs subject to permissions.

Note: For external tables, since they are synchronized to serverless SQL pool asynchronously, there will be a delay until
they appear.

Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/metadata/table

QUESTION 13 #

HOTSPOT
You are building an Azure Stream Analytics job to identify how much time a user spends interacting with a feature on a
webpage.

The job receives events based on user actions on the webpage. Each row of data represents an event. Each event has
a type of either \\’start\\’ or \\’end\\’.

You need to calculate the duration between start and end events.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Hot Area

Box 1: DATEDIFF
DATEDIFF function returns the count (as a signed integer value) of the specified datepart boundaries crossed between
the specified startdate and enddate.
Syntax: DATEDIFF ( datepart , startdate, enddate )

Box 2: LAST
The LAST function can be used to retrieve the last event within a specific condition. In this example, a condition is an
event of type Start, partitioning the search by PARTITION BY user and feature. This way, every user and feature is
treated independently when searching for the Start event. LIMIT DURATION limits the search back in time to 1 hour
between the End and Start events.

Example:
SELECT [user], feature, DATEDIFF( second, LAST(Time) OVER (PARTITION BY [user], feature LIMIT
DURATION(hour, 1) WHEN Event = \\’start\\’), Time) as duration
FROM input TIMESTAMP BY Time
WHERE Event = \\’end\\’

Reference: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-stream-analytics-query-patterns

QUESTION 14 #

HOTSPOT
You are designing a monitoring solution for a fleet of 500 vehicles. Each vehicle has a GPS tracking device that sends
data to an Azure event hub once per minute.

You have a CSV file in an Azure Data Lake Storage Gen2 container. The file maintains the expected geographical area
in which each vehicle should be.

You need to ensure that when a GPS position is outside the expected area, a message is added to another event hub
for processing within 30 seconds. The solution must minimize cost.

What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Box 1: Azure Stream Analytics

Box 2: Hopping Hopping window functions hop forward in time by a fixed period. It may be easy to think of them as
Tumbling windows that can overlap and be emitted more often than the window size. Events can belong to more than
one Hopping window result set. To make a Hopping window the same as a Tumbling window, specify the hop size to be the same as the window size.

Box 3: Point within a polygon

Reference: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions

QUESTION 15 #

HOTSPOT
You need to design the partitions for the product sales transactions. The solution must meet the sales transaction
dataset requirements.

What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Box 1: Sales date
Scenario: Contoso requirements for data integration include:
Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month.
Boundary values must belong to the partition on the right.

Box 2: An Azure Synapse Analytics Dedicated SQL pool
Scenario: Contoso requirements for data integration include:
Ensure that data storage costs and performance are predictable.
The size of a dedicated SQL pool (formerly SQL DW) is determined by Data Warehousing Units (DWU).

Dedicated SQL pool (formerly SQL DW) stores data in relational tables with columnar storage. This format significantly
reduces the data storage costs, and improves query performance.
Synapse analytics dedicated SQL pool

Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-overview-what-is

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