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Pass Guaranteed Authoritative DP-203 - Dumps Data Engineering on Microsoft Azure Collection

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To prepare for the DP-203 Exam, professionals should have a strong understanding of data engineering concepts and experience with Microsoft Azure. Microsoft offers a variety of resources to help professionals prepare for the exam, including study guides, training courses, and practice exams. Additionally, professionals can gain hands-on experience by working on data engineering projects on Microsoft Azure.

To prepare for the Microsoft DP-203 certification exam, you will need to have a solid understanding of Azure data services, including Azure Databricks, Azure Data Factory, Azure Stream Analytics, and Azure Cosmos DB. You will also need to be familiar with data integration and transformation techniques, as well as data security and compliance requirements. Microsoft offers a range of training resources and study materials to help you prepare for the exam, including online courses, practice exams, and virtual labs.

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The DP-203 exam covers several key topics, including designing and implementing data storage solutions, ingesting and transforming data, processing and analyzing data, and monitoring and optimizing data solutions. It also tests candidates' knowledge of Azure data services such as Azure Data Factory, Azure Databricks, Azure Stream Analytics, and Azure Cosmos DB, among others. Successful completion of DP-203 Exam demonstrates that a candidate has the skills and knowledge to design and implement data solutions that meet the business requirements of their organization.

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q21-Q26):

NEW QUESTION # 21
You need to ensure that the Twitter feed data can be analyzed in the dedicated SQL pool. The solution must meet the customer sentiment analytics requirements.
Which three Transaction-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.

Answer:

Explanation:

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

NEW QUESTION # 22
A company plans to use Apache Spark analytics to analyze intrusion detection data.
You need to recommend a solution to analyze network and system activity data for malicious activities and policy violations. The solution must minimize administrative efforts.
What should you recommend?

A. Azure Data Factory
B. Azure Databricks
C. Azure Data Lake Storage
D. Azure HDInsight

Answer: B

Explanation:
Explanation
Three common analytics use cases with Microsoft Azure Databricks
Recommendation engines, churn analysis, and intrusion detection are common scenarios that many organizations are solving across multiple industries. They require machine learning, streaming analytics, and utilize massive amounts of data processing that can be difficult to scale without the right tools.
Recommendation engines, churn analysis, and intrusion detection are common scenarios that many organizations are solving across multiple industries. They require machine learning, streaming analytics, and utilize massive amounts of data processing that can be difficult to scale without the right tools.
Note: Recommendation engines, churn analysis, and intrusion detection are common scenarios that many organizations are solving across multiple industries. They require machine learning, streaming analytics, and utilize massive amounts of data processing that can be difficult to scale without the right tools.
Reference:
https://azure.microsoft.com/es-es/blog/three-critical-analytics-use-cases-with-microsoft-azure-databricks/

NEW QUESTION # 23
You have an Azure Synapse Analytics dedicated SQL pool.
You need to monitor the database for long-running queries and identify which queries are waiting on resources Which dynamic management view should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE; Each correct answer is worth one point.

Answer:

Explanation:

NEW QUESTION # 24
You have an enterprise data warehouse in Azure Synapse Analytics named DW1 on a server named Server1.
You need to verify whether the size of the transaction log file for each distribution of DW1 is smaller than 160 GB.
What should you do?

A. On DW1, execute a query against the sys.database_files dynamic management view.
B. On the master database, execute a query against the sys.dm_pdw_nodes_os_performance_counters dynamic management view.
C. From Azure Monitor in the Azure portal, execute a query against the logs of DW1.

Answer: B

Explanation:
D. Execute a query against the logs of DW1 by using the Get-AzOperationalInsightSearchResult PowerShell cmdlet.
Explanation:
The following query returns the transaction log size on each distribution. If one of the log files is reaching 160 GB, you should consider scaling up your instance or limiting your transaction size.
-- Transaction log size
SELECT
instance_name as distribution_db,
cntr_value*1.0/1048576 as log_file_size_used_GB,
pdw_node_id
FROM sys.dm_pdw_nodes_os_performance_counters
WHERE
instance_name like 'Distribution_%'
AND counter_name = 'Log File(s) Used Size (KB)'
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-monitor

NEW QUESTION # 25
You have the following table named Employees.

You need to calculate the employee_type value based on the hire_date value.
How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Box 1: CASE
CASE evaluates a list of conditions and returns one of multiple possible result expressions.
CASE can be used in any statement or clause that allows a valid expression. For example, you can use CASE in statements such as SELECT, UPDATE, DELETE and SET, and in clauses such as select_list, IN, WHERE, ORDER BY, and HAVING.
Syntax: Simple CASE expression:
CASE input_expression
WHEN when_expression THEN result_expression [ ...n ]
[ ELSE else_result_expression ]
END
Box 2: ELSE
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/language-elements/case-transact-sql

NEW QUESTION # 26
......

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