Microsoft Data Engineering on Microsoft Azure - DP-203 Exam Practice Test
You are building a data flow in Azure Data Factory that upserts data into a table in an Azure Synapse Analytics dedicated SQL pool.
You need to add a transformation to the data flow. The transformation must specify logic indicating when a row from the input data must be upserted into the sink.
Which type of transformation should you add to the data flow?
You need to add a transformation to the data flow. The transformation must specify logic indicating when a row from the input data must be upserted into the sink.
Which type of transformation should you add to the data flow?
Correct Answer: B
Explanation: Only visible for TrainingDump members. You can sign-up / login (it's free).
You are performing exploratory analysis of the bus fare data in an Azure Data Lake Storage Gen2 account by using an Azure Synapse Analytics serverless SQL pool.
You execute the Transact-SQL query shown in the following exhibit.
What do the query results include?
You execute the Transact-SQL query shown in the following exhibit.
What do the query results include?
Correct Answer: C
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.
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.
Correct 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.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-external-tables
You have a data model that you plan to implement in a data warehouse in Azure Synapse Analytics as shown in 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.
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.
Correct Answer:
Explanation:
You have an Azure Data Lake Storage Gen2 container.
Data is ingested into the container, and then transformed by a data integration application. The data is NOT modified after that. Users can read files in the container but cannot modify the files.
You need to design a data archiving solution that meets the following requirements:
New data is accessed frequently and must be available as quickly as possible.
Data that is older than five years is accessed infrequently but must be available within one second when requested.
Data that is older than seven years is NOT accessed. After seven years, the data must be persisted at the lowest cost possible.
Costs must be minimized while maintaining the required availability.
How should you manage the data? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point
Data is ingested into the container, and then transformed by a data integration application. The data is NOT modified after that. Users can read files in the container but cannot modify the files.
You need to design a data archiving solution that meets the following requirements:
New data is accessed frequently and must be available as quickly as possible.
Data that is older than five years is accessed infrequently but must be available within one second when requested.
Data that is older than seven years is NOT accessed. After seven years, the data must be persisted at the lowest cost possible.
Costs must be minimized while maintaining the required availability.
How should you manage the data? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point
Correct Answer:
Explanation:
Box 1: Move to cool storage
Box 2: Move to archive storage
Archive - Optimized for storing data that is rarely accessed and stored for at least 180 days with flexible latency requirements, on the order of hours.
The following table shows a comparison of premium performance block blob storage, and the hot, cool, and archive access tiers.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers Explanation:
Box 1: Replicated
Replicated tables are ideal for small star-schema dimension tables, because the fact table is often distributed on a column that is not compatible with the connected dimension tables. If this case applies to your schema, consider changing small dimension tables currently implemented as round-robin to replicated.
Box 2: Replicated
Box 3: Replicated
Box 4: Hash-distributed
For Fact tables use hash-distribution with clustered columnstore index. Performance improves when two hash tables are joined on the same distribution column.
Reference:
https://azure.microsoft.com/en-us/updates/reduce-data-movement-and-make-your-queries-more-efficient-with- the-general-availability-of-replicated-tables/
https://azure.microsoft.com/en-us/blog/replicated-tables-now-generally-available-in-azure-sql-data-warehouse/
You are creating an Azure Data Factory data flow that will ingest data from a CSV file, cast columns to specified types of data, and insert the data into a table in an Azure Synapse Analytic dedicated SQL pool. The CSV file contains three columns named username, comment, and date.
The data flow already contains the following:
A source transformation.
A Derived Column transformation to set the appropriate types of data.
A sink transformation to land the data in the pool.
You need to ensure that the data flow meets the following requirements:
All valid rows must be written to the destination table.
Truncation errors in the comment column must be avoided proactively.
Any rows containing comment values that will cause truncation errors upon insert must be written to a file in blob storage.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
The data flow already contains the following:
A source transformation.
A Derived Column transformation to set the appropriate types of data.
A sink transformation to land the data in the pool.
You need to ensure that the data flow meets the following requirements:
All valid rows must be written to the destination table.
Truncation errors in the comment column must be avoided proactively.
Any rows containing comment values that will cause truncation errors upon insert must be written to a file in blob storage.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Correct Answer: A,B
Explanation: Only visible for TrainingDump members. You can sign-up / login (it's free).
You have an activity in an Azure Data Factory pipeline. The activity calls a stored procedure in a data warehouse in Azure Synapse Analytics and runs daily.
You need to verify the duration of the activity when it ran last.
What should you use?
You need to verify the duration of the activity when it ran last.
What should you use?
Correct Answer: A
Explanation: Only visible for TrainingDump members. You can sign-up / login (it's free).
You have an Azure Data Factory pipeline shown the following exhibit.
The execution log for the first pipeline run is shown in the following exhibit.
The execution log for the second pipeline run is shown in the following exhibit.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
The execution log for the first pipeline run is shown in the following exhibit.
The execution log for the second pipeline run is shown in the following exhibit.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
You have an Azure data solution that contains an enterprise data warehouse in Azure Synapse Analytics named DW1.
Several users execute ad hoc queries to DW1 concurrently.
You regularly perform automated data loads to DW1.
You need to ensure that the automated data loads have enough memory available to complete quickly and successfully when the adhoc queries run.
What should you do?
Several users execute ad hoc queries to DW1 concurrently.
You regularly perform automated data loads to DW1.
You need to ensure that the automated data loads have enough memory available to complete quickly and successfully when the adhoc queries run.
What should you do?
Correct Answer: B
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You plan to use an Apache Spark pool in Azure Synapse Analytics to load data to an Azure Data Lake Storage Gen2 account.
You need to recommend which file format to use to store the data in the Data Lake Storage account. The solution must meet the following requirements:
* Column names and data types must be defined within the files loaded to the Data Lake Storage account.
* Data must be accessible by using queries from an Azure Synapse Analytics serverless SQL pool.
* Partition elimination must be supported without having to specify a specific partition.
What should you recommend?
You need to recommend which file format to use to store the data in the Data Lake Storage account. The solution must meet the following requirements:
* Column names and data types must be defined within the files loaded to the Data Lake Storage account.
* Data must be accessible by using queries from an Azure Synapse Analytics serverless SQL pool.
* Partition elimination must be supported without having to specify a specific partition.
What should you recommend?
Correct Answer: C
You are monitoring an Azure Stream Analytics job by using metrics in Azure.
You discover that during the last 12 hours, the average watermark delay is consistently greater than the configured late arrival tolerance.
What is a possible cause of this behavior?
You discover that during the last 12 hours, the average watermark delay is consistently greater than the configured late arrival tolerance.
What is a possible cause of this behavior?
Correct Answer: B
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