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Microsoft DP-203 certification exam is intended for data engineers who work with data scientists, data analysts, and business stakeholders to implement data solutions on the Microsoft Azure platform. DP-203 Exam covers various topics such as Azure data storage, Azure data processing, Azure data integration, and data transformation. It also tests your knowledge of key Azure services such as Azure Data Factory, Azure Synapse Analytics, and Azure Stream Analytics.
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The DP-203 Exam covers a wide range of topics related to data engineering on Azure, including data ingestion and processing, data storage, data transformation, and data security. Candidates are expected to have a deep understanding of Azure services, such as Azure Data Factory, Azure Databricks, Azure Stream Analytics, and Azure Synapse Analytics, as well as knowledge of programming languages such as SQL, Python, and Scala. Microsoft Data Engineering on Microsoft Azure Sample Questions (Q117-Q122):NEW QUESTION # 117
You are building a database in an Azure Synapse Analytics serverless SQL pool.
You have data stored in Parquet files in an Azure Data Lake Storage Gen2 container.
Records are structured as shown in the following sample.
{
"id": 123,
"address_housenumber": "19c",
"address_line": "Memory Lane",
"applicant1_name": "Jane",
"applicant2_name": "Dev"
}
The records contain two applicants at most.
You need to build a table that includes only the address fields.
How should you complete the Transact-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
Explanation
Box 1: CREATE EXTERNAL TABLE
An external table points to data located in Hadoop, Azure Storage blob, or Azure Data Lake Storage. External tables are used to read data from files or write data to files in Azure Storage. With Synapse SQL, you can use external tables to read external data using dedicated SQL pool or serverless SQL pool.
Syntax:
CREATE EXTERNAL TABLE { database_name.schema_name.table_name | schema_name.table_name | table_name } ( <column_definition> [ ,...n ] ) WITH ( LOCATION = 'folder_or_filepath', DATA_SOURCE = external_data_source_name, FILE_FORMAT = external_file_format_name Box 2. OPENROWSET When using serverless SQL pool, CETAS is used to create an external table and export query results to Azure Storage Blob or Azure Data Lake Storage Gen2.
Example:
AS
SELECT decennialTime, stateName, SUM(population) AS population
FROM
OPENROWSET(BULK
'https://azureopendatastorage.blob.core.windows.net/censusdatacontainer/release/us_population_county/year=*/* FORMAT='PARQUET') AS [r] GROUP BY decennialTime, stateName GO Reference: https://docs.microsoft.com/en-us ... les-external-tables
NEW QUESTION # 118
You have an Azure Data Factory pipeline that is triggered hourly.
The pipeline has had 100% success for the past seven days.
The pipeline execution fails, and two retries that occur 15 minutes apart also fail. The third failure returns the following error.
What is a possible cause of the error?
A. From 06:00 to 07:00 on January 10, 2021, there was no data in wwi/BIKES/CARBON.
B. The parameter used to generate year=2021/month=01/day=10/hour=06 was incorrect.
C. The pipeline was triggered too early.
D. From 06:00 to 07:00 on January 10, 2021, the file format of data in wwi/BIKES/CARBON was incorrect.
Answer: B
NEW QUESTION # 119
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:
Reference: https://docs.microsoft.com/en-us ... s/case-transact-sql
NEW QUESTION # 120
You have an enterprise data warehouse in Azure Synapse Analytics that contains a table named FactOnlineSales. The table contains data from the start of 2009 to the end of 2012.
You need to improve the performance of queries against FactOnlineSales by using table partitions. The solution must meet the following requirements:
Create four partitions based on the order date.
Ensure that each partition contains all the orders places during a given calendar year.
How should you complete the T-SQL command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
Explanation:
Range Left or Right, both are creating similar partition but there is difference in comparison For example: in this scenario, when you use LEFT and 20100101,20110101,20120101 Partition will be, datecol<=20100101, datecol>20100101 and datecol<=20110101, datecol>20110101 and datecol<=20120101, datecol>20120101 But if you use range RIGHT and 20100101,20110101,20120101 Partition will be, datecol<20100101, datecol>=20100101 and datecol<20110101, datecol>=20110101 and datecol<20120101, datecol>=20120101 In this example, Range RIGHT will be suitable for calendar comparison Jan 1st to Dec 31st Reference: https://docs.microsoft.com/en-us ... ql?view=sql-server- ver15
NEW QUESTION # 121
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 Answer:
Explanation:
Explanation
Box 1: Hash-distributed
Box 2: ProductKey
ProductKey is used extensively in joins.
Hash-distributed tables improve query performance on large fact tables.
Box 3: Round-robin
Box 4: RegionKey
Round-robin tables are useful for improving loading speed.
Consider using the round-robin distribution for your table in the following scenarios:
* When getting started as a simple starting point since it is the default
* If there is no obvious joining key
* If there is not good candidate column for hash distributing the table
* If the table does not share a common join key with other tables
* If the join is less significant than other joins in the query
* When the table is a temporary staging table
Note: A distributed table appears as a single table, but the rows are actually stored across 60 distributions. The rows are distributed with a hash or round-robin algorithm.
Reference: https://docs.microsoft.com/en-us ... e-tables-distribute
