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Microsoft DP-203 Sample Question Answers
Question # 1
You plan to build a structured streaming solution in Azure Databricks. The solution willcount new events in five-minute intervals and report only events that arrive during theinterval. The output will be sent to a Delta Lake table.Which output mode should you use?
A. complete B. update C. append
Answer: C
Explanation: Append Mode: Only new rows appended in the result table since the last
trigger are written to external storage. This is applicable only for the queries where existing
rows in the Result Table are not expected to change.
You need to trigger an Azure Data Factory pipeline when a file arrives in an Azure DataLake Storage Gen2 container.Which resource provider should you enable?
A. Microsoft.Sql B. Microsoft-Automation C. Microsoft.EventGrid D. Microsoft.EventHub
Answer: C
Explanation:
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
storage account, such as the arrival or deletion of a file in Azure Blob Storage account.
Data Factory natively integrates with Azure Event Grid, which lets you trigger pipelines on
You are designing an Azure Databricks interactive cluster. The cluster will be usedinfrequently and will be configured for auto-termination.You need to ensure that the cluster configuration is retained indefinitely after the cluster isterminated. The solution must minimize costsWhat should you do?
A. Clone the cluster after it is terminated. B. Terminate the cluster manually when processing completes. C. Create an Azure runbook that starts the cluster every 90 days. D. Pin the cluster.
Answer: D
Explanation:
To keep an interactive cluster configuration even after it has been terminated for more than
30 days, an
administrator can pin a cluster to the cluster list.
You have an enterprise data warehouse in Azure Synapse Analytics named DW1 on aserver named Server1.You need to verify whether the size of the transaction log file for each distribution of DW1 issmaller than 160 GB.What should you do?
A. On the master database, execute a query against thesys.dm_pdw_nodes_os_performance_counters dynamic management view. B. From Azure Monitor in the Azure portal, execute a query against the logs of DW1. C. On DW1, execute a query against the sys.database_files dynamic management view. D. Execute a query against the logs of DW1 by using the Get-AzOperationalInsightSearchResult PowerShell cmdlet.
Answer: A
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
You are designing a financial transactions table in an Azure Synapse Analytics dedicatedSQL pool. The table will have a clustered columnstore index and will include the followingcolumns:TransactionType: 40 million rows per transaction typeCustomerSegment: 4 million per customer segmentTransactionMonth: 65 million rows per monthAccountType: 500 million per account typeYou have the following query requirements:Analysts will most commonly analyze transactions for a given month.Transactions analysis will typically summarize transactions by transaction type,customer segment, and/or account typeYou need to recommend a partition strategy for the table to minimize query times.On which column should you recommend partitioning the table?
A. CustomerSegment B. AccountType C. TransactionType D. TransactionMonth
Answer: D
Explanation:
For optimal compression and performance of clustered columnstore tables, a minimum of 1
million rows per distribution and partition is needed. Before partitions are created,
dedicated SQL pool already divides each table into 60 distributed databases.
Example: Any partitioning added to a table is in addition to the distributions created behind
the scenes. Using this example, if the sales fact table contained 36 monthly partitions, and
given that a dedicated SQL pool has 60 distributions, then the sales fact table should
contain 60 million rows per month, or 2.1 billion rows when all months are populated. If a
table contains fewer than the recommended minimum number of rows per partition,
consider using fewer partitions in order to increase the number of rows per partition.
Question # 6
You plan to ingest streaming social media data by using Azure Stream Analytics. The datawill be stored in files in Azure Data Lake Storage, and then consumed by using AzureDatiabricks and PolyBase in Azure Synapse Analytics.You need to recommend a Stream Analytics data output format to ensure that the queriesfrom Databricks and PolyBase against the files encounter the fewest possible errors. Thesolution must ensure that the tiles can be queried quickly and that the data type informationis retained.What should you recommend?
Note: This question is part of a series of questions that present the same scenario.Each question in the series contains a unique solution that might meet the statedgoals. Some question sets might have more than one correct solution, while othersmight not have a correct solution.After you answer a question in this section, you will NOT be able to return to it. As aresult, these questions will not appear in the review screen.You plan to create an Azure Databricks workspace that has a tiered structure. Theworkspace will contain the following three workloads:A workload for data engineers who will use Python and SQL.A workload for jobs that will run notebooks that use Python, Scala, and SOL.A workload that data scientists will use to perform ad hoc analysis in Scala and R.The enterprise architecture team at your company identifies the following standards forDatabricks environments: The data engineers must share a cluster.The job cluster will be managed by using a request process whereby datascientists and data engineers provide packaged notebooks for deployment to thecluster.All the data scientists must be assigned their own cluster that terminatesautomatically after 120 minutes of inactivity. Currently, there are three datascientists.You need to create the Databricks clusters for the workloads.Solution: You create a Standard cluster for each data scientist, a High Concurrency clusterfor the data engineers, and a Standard cluster for the jobs.Does this meet the goal?
A. Yes B. No
Answer: B
Explanation:
We would need a High Concurrency cluster for the jobs.
Note:
Standard clusters are recommended for a single user. Standard can run workloads
developed in any language:
Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high
concurrency clusters are that
they provide Apache Spark-native fine-grained sharing for maximum resource utilization
You have an Azure Stream Analytics job.You need to ensure that the job has enough streaming units provisionedYou configure monitoring of the SU % Utilization metric.Which two additional metrics should you monitor? Each correct answer presents part of thesolution.NOTE Each correct selection is worth one point
A. Out of order Events B. Late Input Events C. Baddogged Input Events D. Function Events
Answer: C
Question # 9
You are developing a solution that will stream to Azure Stream Analytics. The solution willhave both streaming data and reference data.Which input type should you use for the reference data?
A. Azure Cosmos DB B. Azure Blob storage C. Azure IoT Hub D. Azure Event Hubs
Answer: B
Explanation:
Stream Analytics supports Azure Blob storage and Azure SQL Database as the storage
You have an Azure Synapse Analytics dedicated SQL pool that contains a table namedTable1.You have files that are ingested and loaded into an Azure Data Lake Storage Gen2container named container1.You plan to insert data from the files into Table1 and azure Data Lake Storage Gen2container named container1.You plan to insert data from the files into Table1 and transform the data. Each row of datain the files will produce one row in the serving layer of Table1.You need to ensure that when the source data files are loaded to container1, the DateTimeis stored as an additional column in Table1.Solution: You use a dedicated SQL pool to create an external table that has a additionalDateTime column.Does this meet the goal?
A. Yes B. No
Answer: A
Question # 11
You plan to perform batch processing in Azure Databricks once daily.Which type of Databricks cluster should you use?
A. High Concurrency B. automated C. interactive
Answer: B
Explanation:
Azure Databricks has two types of clusters: interactive and automated. You use interactive
clusters to analyze data collaboratively with interactive notebooks. You use automated
You have an Azure Synapse Analytics dedicated SQL pool named Pool1 and a databasenamed DB1. DB1 contains a fact table named Table1.You need to identify the extent of the data skew in Table1.What should you do in Synapse Studio?
A. Connect to the built-in pool and query sysdm_pdw_sys_info. B. Connect to Pool1 and run DBCC CHECKALLOC. C. Connect to the built-in pool and run DBCC CHECKALLOC. D. Connect to Pool! and query sys.dm_pdw_nodes_db_partition_stats.
Answer: D
Explanation:
Microsoft recommends use of sys.dm_pdw_nodes_db_partition_stats to analyze any
You are creating a new notebook in Azure Databricks that will support R as the primarylanguage but will also support Scale and SOL Which switch should you use to switchbetween languages?
A. @<Language> B. %<Language> C. \\(<Language>) D. \\(<Language>)
Answer: B
Explanation:
To change the language in Databricks’ cells to either Scala, SQL, Python or R, prefix the
You use Azure Data Lake Storage Gen2.You need to ensure that workloads can use filter predicates and column projections to filterdata at the time the data is read from disk.Which two actions should you perform? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.
A. Reregister the Microsoft Data Lake Store resource provider. B. Reregister the Azure Storage resource provider. C. Create a storage policy that is scoped to a container. D. Register the query acceleration feature. E. Create a storage policy that is scoped to a container prefix filter.
Answer: B,D
Question # 15
Note: This question is part of a series of questions that present the same scenario. Eachquestion in the series contains a unique solution that might meet the stated goals. Somequestion sets might have more than one correct solution, while others might not have acorrect solution.After you answer a question in this scenario, you will NOT be able to return to it. As aresult, these questions will not appear in the review screen.You have an Azure Storage account that contains 100 GB of files. The files contain textand numerical values. 75% of the rows contain description data that has an average lengthof 1.1 MB.You plan to copy the data from the storage account to an enterprise data warehouse inAzure Synapse Analytics.You need to prepare the files to ensure that the data copies quickly.Solution: You convert the files to compressed delimited text files.Does this meet the goal?
A. Yes B. No
Answer: A
Explanation:
All file formats have different performance characteristics. For the fastest load, use
You manage an enterprise data warehouse in Azure Synapse Analytics.Users report slow performance when they run commonly used queries. Users do not reportperformance changes for infrequently used queries.You need to monitor resource utilization to determine the source of the performanceissues.Which metric should you monitor?
A. Data IO percentage B. Local tempdb percentage C. Cache used percentage D. DWU percentage
Answer: C
Explanation:
Monitor and troubleshoot slow query performance by determining whether your workload is
optimally leveraging the adaptive cache for dedicated SQL pools.
You are designing an Azure Databricks cluster that runs user-defined local processes. Youneed to recommend a cluster configuration that meets the following requirements:• Minimize query latency.• Maximize the number of users that can run queues on the cluster at the same time «Reduce overall costs without compromising other requirementsWhich cluster type should you recommend?
A. Standard with Auto termination B. Standard with Autoscaling C. High Concurrency with Autoscaling D. High Concurrency with Auto Termination
Answer: C
Explanation:
A High Concurrency cluster is a managed cloud resource. The key benefits of High
Concurrency clusters are that they provide fine-grained sharing for maximum resource
utilization and minimum query latencies.
Databricks chooses the appropriate number of workers required to run your job. This is
referred to as autoscaling. Autoscaling makes it easier to achieve high cluster utilization,
because you don’t need to provision the cluster to match a workload.
You have an Azure Synapse Analytics dedicated SQL pool that contains a large fact table.The table contains 50 columns and 5 billion rows and is a heap.Most queries against the table aggregate values from approximately 100 million rows andreturn only two columns.You discover that the queries against the fact table are very slow.Which type of index should you add to provide the fastest query times?
A. nonclustered columnstore B. clustered columnstore C. nonclustered D. clustered
Answer: B
Explanation:
Clustered columnstore indexes are one of the most efficient ways you can store your data
in dedicated SQL pool.
Columnstore tables won't benefit a query unless the table has more than 60 million rows.
You have an Azure Synapse Analystics dedicated SQL pool that contains a table namedContacts. Contacts contains a column named Phone.You need to ensure that users in a specific role only see the last four digits of a phonenumber when querying the Phone column.What should you include in the solution?
A. a default value B. dynamic data masking C. row-level security (RLS) D. column encryption E. table partitions
Answer: B
Explanation:
Dynamic data masking helps prevent unauthorized access to sensitive data by enabling
customers to designate how much of the sensitive data to reveal with minimal impact on
the application layer. It’s a policy-based security feature that hides the sensitive data in the
result set of a query over designated database fields, while the data in the database is not
You need to design an Azure Synapse Analytics dedicated SQL pool that meets thefollowing requirements:Can return an employee record from a given point in time.Maintains the latest employee information.Minimizes query complexity.How should you model the employee data?
A. as a temporal table B. as a SQL graph table C. as a degenerate dimension table D. as a Type 2 slowly changing dimension (SCD) table
Answer: D
Explanation:
A Type 2 SCD supports versioning of dimension members. Often the source system
doesn't store versions, so the data warehouse load process detects and manages changes
in a dimension table. In this case, the dimension table must use a surrogate key to provide
a unique reference to a version of the dimension member. It also includes columns that
define the date range validity of the version (for example, StartDate and EndDate) and
possibly a flag column (for example, IsCurrent) to easily filter by current dimension
You are monitoring an Azure Stream Analytics job.The Backlogged Input Events count has been 20 for the last hour.You need to reduce the Backlogged Input Events count.What should you do?
A. Drop late arriving events from the job. B. Add an Azure Storage account to the job. C. Increase the streaming units for the job. D. Stop the job.
Answer: C
Explanation:
General symptoms of the job hitting system resource limits include:
If the backlog event metric keeps increasing, it’s an indicator that the system
resource is constrained (either because of output sink throttling, or high CPU).
Note: Backlogged Input Events: Number of input events that are backlogged. A non-zero
value for this metric implies that your job isn't able to keep up with the number of incoming
events. If this value is slowly increasing or consistently non-zero, you should scale out your
You are designing a dimension table for a data warehouse. The table will track the value ofthe dimension attributes over time and preserve the history of the data by adding new rowsas the data changes.Which type of slowly changing dimension (SCD) should use?
A. Type 0 B. Type 1 C. Type 2 D. Type 3
Answer: C
Explanation:
Type 2 - Creating a new additional record. In this methodology all history of dimension
changes is kept in the database. You capture attribute change by adding a new row with a
new surrogate key to the dimension table. Both the prior and new rows contain as
attributes the natural key(or other durable identifier). Also 'effective date' and 'current
indicator' columns are used in this method. There could be only one record with current
indicator set to 'Y'. For 'effective date' columns, i.e. start_date and end_date, the end_date
for current record usually is set to value 9999-12-31. Introducing changes to the
dimensional model in type 2 could be very expensive database operation so it is not
recommended to use it in dimensions where a new attribute could be added in the future.
You have an Azure Data Factory that contains 10 pipelines.You need to label each pipeline with its main purpose of either ingest, transform, or load.The labels must be available for grouping and filtering when using the monitoringexperience in Data Factory.What should you add to each pipeline?
A. a resource tag B. a correlation ID C. a run group ID D. an annotation
Answer: D
Explanation:
Annotations are additional, informative tags that you can add to specific factory resources:
pipelines, datasets, linked services, and triggers. By adding annotations, you can easily
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 consistentlygreater than the configured late arrival tolerance.What is a possible cause of this behavior?
A. Events whose application timestamp is earlier than their arrival time by more than fiveminutes arrive as inputs. B. There are errors in the input data. C. The late arrival policy causes events to be dropped. D. The job lacks the resources to process the volume of incoming data.
Answer: D
Explanation:
Watermark Delay indicates the delay of the streaming data processing job.
There are a number of resource constraints that can cause the streaming pipeline to slow
down. The watermark delay metric can rise due to:
Not enough processing resources in Stream Analytics to handle the volume of
input events. To scale up resources, see Understand and adjust Streaming Units.
Not enough throughput within the input event brokers, so they are throttled. For
possible solutions, see Automatically scale up Azure Event Hubs throughput units.
Output sinks are not provisioned with enough capacity, so they are throttled. The
possible solutions vary widely based on the flavor of output service being used.
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 NOTrequire 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 Synapseworkspace. D. Create an Azure key vault in the Azure subscription grant access to the pool.
Answer: B
Explanation:
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.