microsoft dp-203 online test

Question 1 Topic 1, Case Study 1Case Study Question View Case

HOTSPOT
You need to design a data storage structure 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.
Hot Area:

Answer:

Explanation:
Box 1: Hash Scenario:
Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.
A hash distributed table can deliver the highest query performance for joins and aggregations on large tables.
Box 2: Set the distribution column to the sales date.
Scenario: 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.
Reference: https://rajanieshkaushikk.com/2020/09/09/how-to-choose-right-data-distribution-strategy-for-azure-synapse/

Question 2 Topic 1, Case Study 1Case Study Question View Case

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.
Select and Place:

Answer:

Explanation:
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 Topic 1, Case Study 1Case Study Question View Case

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.
Hot Area:

Answer:

Explanation:
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

Question 4 Topic 1, Case Study 1Case Study Question View Case

You need to implement the surrogate key for the retail store table. The solution must meet the sales transaction dataset
requirements.
What should you create?

• A. a table that has an IDENTITY property
• B. a system-versioned temporal table
• C. a user-defined SEQUENCE object
• D. a table that has a FOREIGN KEY constraint

Answer:

A

Explanation:
Scenario: Implement a surrogate key to account for changes to the retail store addresses.
A surrogate key on a table is a column with a unique identifier for each row. The key is not generated from the table data.
Data modelers like to create surrogate keys on their tables when they design data warehouse models. You can use the
IDENTITY property to achieve this goal simply and effectively without affecting load performance.
Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-identity

Question 5 Topic 1, Case Study 1Case Study Question View Case

HOTSPOT
You need to design an analytical storage solution for the transactional data. 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.
Hot Area:

Answer:

Explanation:
Box 1: Round-robin
Round-robin tables are useful for improving loading speed.
Scenario: Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by
month.
Box 2: Hash
Hash-distributed tables improve query performance on large fact tables.
Scenario:
You plan to create a promotional table that will contain a promotion ID. The promotion ID will be associated to a specific

product. The product will be identified by a product ID. The table will be approximately 5 GB.
Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.

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

Question 6 Topic 1, Case Study 1Case Study Question View Case

HOTSPOT
You need to implement an Azure Synapse Analytics database object for storing the sales transactions data. The solution
must meet the sales transaction dataset requirements.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

Answer:

Explanation:
Box 1: Create table
Scenario: Load the sales transaction dataset to Azure Synapse Analytics
Box 2: RANGE RIGHT FOR VALUES
Scenario: 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.
RANGE RIGHT: Specifies the boundary value belongs to the partition on the right (higher values). FOR VALUES (
boundary_value [,...n] ): Specifies the boundary values for the partition.
Scenario: Load the sales transaction dataset to Azure Synapse Analytics.
Contoso identifies the following requirements for the sales transaction dataset:
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. Ensure that queries joining and filtering sales transaction

records based on product ID complete as quickly as possible. Implement a surrogate key to account for changes to the

retail store addresses.
Ensure that data storage costs and performance are predictable. Minimize how long it takes to remove old records.


Reference: https://docs.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse

Question 7 Topic 1, Case Study 1Case Study Question View Case

You need to design a data retention solution for the Twitter feed data records. The solution must meet the customer
sentiment analytics requirements.
Which Azure Storage functionality should you include in the solution?

• A. change feed
• B. soft delete
• C. time-based retention
• D. lifecycle management

Answer:

D

Explanation:
Scenario: Purge Twitter feed data records that are older than two years.
Data sets have unique lifecycles. Early in the lifecycle, people access some data often. But the need for access often drops
drastically as the data ages. Some data remains idle in the cloud and is rarely accessed once stored. Some data sets expire
days or months after creation, while other data sets are actively read and modified throughout their lifetimes. Azure Storage
lifecycle management offers a rule-based policy that you can use to transition blob data to the appropriate access tiers or to
expire data at the end of the data lifecycle.
Reference: https://docs.microsoft.com/en-us/azure/storage/blobs/lifecycle-management-overview

Question 8 Topic 2, Case Study 2Case Study Question View Case

What should you recommend to prevent users outside the Litware on-premises network from accessing the analytical data
store?

• A. a server-level virtual network rule
• B. a database-level virtual network rule
• C. a server-level firewall IP rule
• D. a database-level firewall IP rule

Answer:

C

Explanation:
Scenario:
Ensure that the analytical data store is accessible only to the company's on-premises network and Azure services.


Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure.
Since Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure, they
will have to create firewall IP rules to allow connection from the IP ranges of the on-premise network. They can also use the
firewall rule 0.0.0.0 to allow access from Azure services.
Reference: https://docs.microsoft.com/en-us/azure/sql-database/sql-database-vnet-service-endpoint-rule-overview

Question 9 Topic 2, Case Study 2Case Study Question View Case

What should you recommend using to secure sensitive customer contact information?

• A. Transparent Data Encryption (TDE)
• B. row-level security
• C. column-level security
• D. data sensitivity labels

Answer:

D

Explanation:
Scenario: Limit the business analysts access to customer contact information, such as phone numbers, because this type of
data is not analytically relevant.
Labeling: You can apply sensitivity-classification labels persistently to columns by using new metadata attributes that have
been added to the SQL Server database engine. This metadata can then be used for advanced, sensitivity-based auditing
and protection scenarios.
Incorrect Answers:
A: Transparent Data Encryption (TDE) encrypts SQL Server, Azure SQL Database, and Azure Synapse Analytics data files,
known as encrypting data at rest. TDE does not provide encryption across communication channels.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/data-discovery-and-classification-overview
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-security-overview

Question 10 Topic 3, Mixed Questions

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] [smallint] NULL
• B. [ManagerEmployeeKey] [smallint] NULL
• C. [ManagerEmployeeKey] [int] NULL
• D. [ManagerName] [varchar](200) NULL

Answer:

C

Explanation:
We need an extra column to identify the Manager. Use the data type as the EmployeeKey column, an int column.
Reference: https://docs.microsoft.com/en-us/analysis-services/tabular-models/hierarchies-ssas-tabular