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DP-203 Dumps 2024 - New Microsoft DP-203 Exam Questions
Data Engineering on Microsoft Azure Exam Certification Details:
| Books / Training | DP-203T00: Data Engineering on Microsoft Azure |
| Exam Price | $165 (USD) |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Sample Questions | Data Engineering on Microsoft Azure Sample Questions |
NEW QUESTION # 39
You have an Azure subscription that contains the following resources:
An Azure Active Directory (Azure AD) tenant that contains a security group named Group1 An Azure Synapse Analytics SQL pool named Pool1 You need to control the access of Group1 to specific columns and rows in a table in Pool1.
Which Transact-SQL commands should you use? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/column-level-security
NEW QUESTION # 40
You have an Azure subscription that contains an Azure Data Lake Storage Gen2 account named storage1.
Storage1 contains a container named container1. Container1 contains a directory named directory1. Directory1 contains a file named file1.
You have an Azure Active Directory (Azure AD) user named User1 that is assigned the Storage Blob Data Reader role for storage1.
You need to ensure that User1 can append data to file1. The solution must use the principle of least privilege.
Which permissions should you grant? To answer, drag the appropriate permissions to the correct resources.
Each permission 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.
Answer:
Explanation:
Explanation
Box 1: Execute
If you are granting permissions by using only ACLs (no Azure RBAC), then to grant a security principal read or write access to a file, you'll need to give the security principal Execute permissions to the root folder of the container, and to each folder in the hierarchy of folders that lead to the file.
Box 2: Execute
On Directory: Execute (X): Required to traverse the child items of a directory Box 3: Write On file: Write (W): Can write or append to a file.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-access-control
NEW QUESTION # 41
You plan to create an Azure Data Lake Storage Gen2 account
You need to recommend a storage solution that meets the following requirements:
* Provides the highest degree of data resiliency
* Ensures that content remains available for writes if a primary data center fails What should you include in the recommendation? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
NEW QUESTION # 42
You have an Azure data factory named ADM that contains a pipeline named Pipelwe1 Pipeline! must execute every 30 minutes with a 15-minute offset.
Vou need to create a trigger for Pipehne1. The trigger must meet the following requirements:
* Backfill data from the beginning of the day to the current time.
* If Pipeline1 fairs, ensure that the pipeline can re-execute within the same 30-mmute period.
* Ensure that only one concurrent pipeline execution can occur.
* Minimize de4velopment and configuration effort
Which type of trigger should you create?
- A. tumbling window
- B. event-based
- C. schedule
- D. manual
Answer: C
NEW QUESTION # 43
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.
Answer:
Explanation:
Explanation
Graphical user interface, text, application, table Description automatically generated
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.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-distribu
NEW QUESTION # 44
You have an Azure subscription that contains a logical Microsoft SQL server named Server1. Server1 hosts an Azure Synapse Analytics SQL dedicated pool named Pool1.
You need to recommend a Transparent Data Encryption (TDE) solution for Server1. The solution must meet the following requirements:
* Track the usage of encryption keys.
* Maintain the access of client apps to Pool1 in the event of an Azure datacenter outage that affects the availability of the encryption keys.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: TDE with customer-managed keys
Customer-managed keys are stored in the Azure Key Vault. You can monitor how and when your key vaults are accessed, and by whom. You can do this by enabling logging for Azure Key Vault, which saves information in an Azure storage account that you provide.
Box 2: Create and configure Azure key vaults in two Azure regions
The contents of your key vault are replicated within the region and to a secondary region at least 150 miles away, but within the same geography to maintain high durability of your keys and secrets.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/security/workspaces-encryption
https://docs.microsoft.com/en-us/azure/key-vault/general/logging
NEW QUESTION # 45
You have an Azure Synapse Analytics dedicated SQL pool named Pool1. Pool1 contains a fact table named Tablet. Table1 contains sales dat a. Sixty-five million rows of data are added to Table1 monthly.
At the end of each month, you need to remove data that is older than 36 months. The solution must minimize how long it takes to remove the data.
How should you partition Table1, and how should you remove the old data? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 46
You plan to perform batch processing in Azure Databricks once daily.
Which type of Databricks cluster should you use?
- A. automated
- B. High Concurrency
- C. interactive
Answer: C
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 clusters to run fast and robust automated jobs.
Example: Scheduled batch workloads (data engineers running ETL jobs)
This scenario involves running batch job JARs and notebooks on a regular cadence through the Databricks platform.
The suggested best practice is to launch a new cluster for each run of critical jobs. This helps avoid any issues (failures, missing SLA, and so on) due to an existing workload (noisy neighbor) on a shared cluster.
Reference:
https://docs.databricks.com/administration-guide/cloud-configurations/aws/cmbp.html#scenario-3-scheduled-batch-workloads-data-engineers-running-etl-jobs
NEW QUESTION # 47
You are designing an application that will store petabytes of medical imaging data When the data is first created, the data will be accessed frequently during the first week. After one month, the data must be accessible within 30 seconds, but files will be accessed infrequently. After one year, the data will be accessed infrequently but must be accessible within five minutes.
You need to select a storage strategy for the dat
a. The solution must minimize costs.
Which storage tier should you use for each time frame? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers
NEW QUESTION # 48
You plan to create a real-time monitoring app that alerts users when a device travels more than 200 meters away from a designated location.
You need to design an Azure Stream Analytics job to process the data for the planned app. The solution must minimize the amount of code developed and the number of technologies used.
What should you include in the Stream Analytics job? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-get-started-with-azure-stream-analytics-to-process-data-from-iot-devices
https://docs.microsoft.com/en-us/azure/stream-analytics/geospatial-scenarios
NEW QUESTION # 49
You have an Azure Data Lake Storage Gen 2 account named storage1.
You need to recommend a solution for accessing the content in storage1. The solution must meet the following requirements:
List and read permissions must be granted at the storage account level.
Additional permissions can be applied to individual objects in storage1.
Security principals from Microsoft Azure Active Directory (Azure AD), part of Microsoft Entra, must be used for authentication.
What should you use? To answer, drag the appropriate components to the correct requirements. Each component 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:
NEW QUESTION # 50
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 system-versioned temporal table
- B. a user-defined SEQUENCE object
- C. a table that has a FOREIGN KEY constraint
- D. a table that has an IDENTITY property
Answer: D
Explanation:
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
NEW QUESTION # 51
You need to schedule an Azure Data Factory pipeline to execute when a new file arrives in an Azure Data Lake Storage Gen2 container.
Which type of trigger should you use?
- A. tumbling window
- B. on-demand
- C. schedule
- D. event
Answer: A
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.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-event-trigger
NEW QUESTION # 52
You are building an Azure Stream Analytics job that queries reference data from a product catalog file. The file is updated daily.
The reference data input details for the file are shown in the Input exhibit. (Click the Input tab.)
The storage account container view is shown in the Refdata exhibit. (Click the Refdata tab.)
You need to configure the Stream Analytics job to pick up the new reference data.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-use-reference-data
NEW QUESTION # 53
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 NOT require modifying applications that query the data.
What should you do?
- A. Create an Azure key vault in the Azure subscription grant access to the pool.
- B. Enable encryption at rest for the Azure Data Lake Storage Gen2 account.
- C. Enable Transparent Data Encryption (TDE) for the pool.
- D. Use a customer-managed key to enable double encryption for the Azure Synapse workspace.
Answer: C
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.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-overviewmanage-security
Topic 2, Contoso
Transactional Date
Contoso has three years of customer, transactional, operation, sourcing, and supplier data comprised of 10 billion records stored across multiple on-premises Microsoft SQL Server servers. The SQL server instances contain data from various operational systems. The data is loaded into the instances by using SQL server integration Services (SSIS) packages.
You estimate that combining all product sales transactions into a company-wide sales transactions dataset will result in a single table that contains 5 billion rows, with one row per transaction.
Most queries targeting the sales transactions data will be used to identify which products were sold in retail stores and which products were sold online during different time period. Sales transaction data that is older than three years will be removed monthly.
You plan to create a retail store table that will contain the address of each retail store. The table will be approximately 2 MB. Queries for retail store sales will include the retail store addresses.
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.
Streaming Twitter Data
The ecommerce department at Contoso develops and Azure logic app that captures trending Twitter feeds referencing the company's products and pushes the products to Azure Event Hubs.
Planned Changes
Contoso plans to implement the following changes:
* Load the sales transaction dataset to Azure Synapse Analytics.
* Integrate on-premises data stores with Azure Synapse Analytics by using SSIS packages.
* Use Azure Synapse Analytics to analyze Twitter feeds to assess customer sentiments about products.
Sales Transaction Dataset Requirements
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.
Customer Sentiment Analytics Requirement
Contoso identifies the following requirements for customer sentiment analytics:
* Allow Contoso users to use PolyBase in an A/ure 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 A/ureAD credentials.
* Maximize the throughput of ingesting Twitter feeds from Event Hubs to Azure Storage without purchasing additional throughput or capacity units.
* Store Twitter feeds in Azure Storage by using Event Hubs Capture. The feeds will be converted into Parquet files.
* Ensure that the data store supports Azure AD-based access control down to the object level.
* Minimize administrative effort to maintain the Twitter feed data records.
* Purge Twitter feed data records;itftaitJ are older than two years.
Data Integration Requirements
Contoso identifies the following requirements for data integration:
Use an Azure service that leverages the existing SSIS packages to ingest on-premises data into datasets stored in a dedicated SQL pool of Azure Synaps Analytics and transform the data.
Identify a process to ensure that changes to the ingestion and transformation activities can be version controlled and developed independently by multiple data engineers.
NEW QUESTION # 54
You plan to implement an Azure Data Lake Gen2 storage account.
You need to ensure that the data lake will remain available if a data center fails in the primary Azure region.
The solution must minimize costs.
Which type of replication should you use for the storage account?
- A. geo-zone-redundant storage (GZRS)
- B. locally-redundant storage (LRS)
- C. zone-redundant storage (ZRS)
- D. geo-redundant storage (GRS)
Answer: B
Explanation:
Explanation
Locally redundant storage (LRS) copies your data synchronously three times within a single physical location in the primary region. LRS is the least expensive replication option Reference:
https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy
NEW QUESTION # 55
You have an Azure Storage account that generates 200,000 new files daily. The file names have a format of {YYYY}/{MM}/{DD}/{HH}/{CustomerID}.csv.
You need to design an Azure Data Factory solution that will load new data from the storage account to an Azure Data Lake once hourly. The solution must minimize load times and costs.
How should you configure the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics
NEW QUESTION # 56
You are building an Azure Stream Analytics job to retrieve game data.
You need to ensure that the job returns the highest scoring record for each five-minute time interval of each game.
How should you complete the Stream Analytics query? To answer, select the appropriate options in the answer are a.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/topone-azure-stream-analytics
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions
NEW QUESTION # 57
You are developing an Azure Synapse Analytics pipeline that will include a mapping data flow named Dataflow1. Dataflow1 will read customer data from an external source and use a Type 1 slowly changing dimension (SCO) when loading the data into a table named DimCustomer1 in an Azure Synapse Analytics dedicated SQL pool.
You need to ensure that Dataflow1 can perform the following tasks:
* Detect whether the data of a given customer has changed in the DimCustomer table.
* Perform an upsert to the DimCustomer table.
Which type of transformation should you use for each task? To answer, select the appropriate options in the answer area NOTE; Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 58
You are designing the folder structure for an Azure Data Lake Storage Gen2 account.
You identify the following usage patterns:
* Users will query data by using Azure Synapse Analytics serverless SQL pools and Azure Synapse Analytics serverless Apache Spark pods.
* Most queries will include a filter on the current year or week.
* Data will be secured by data source.
You need to recommend a folder structure that meets the following requirements:
* Supports the usage patterns
* Simplifies folder security
* Minimizes query times
Which folder structure should you recommend?
- A.
- B.
- C.
- D.
- E.
Answer: C
Explanation:
Data will be secured by data source. -> Use DataSource as top folder.
Most queries will include a filter on the current year or week -> Use \YYYY\WW\ as subfolders.
Common Use Cases
A common use case is to filter data stored in a date (and possibly time) folder structure such as /YYYY/MM/DD/ or /YYYY/MM/YYYY-MM-DD/. As new data is generated/sent/copied/moved to the storage account, a new folder is created for each specific time period. This strategy organises data into a maintainable folder structure.
NEW QUESTION # 59
You have an Azure Data Lake Storage Gen2 account named adls2 that is protected by a virtual network.
You are designing a SQL pool in Azure Synapse that will use adls2 as a source.
What should you use to authenticate to adls2?
- A. a shared access signature (SAS)
- B. a managed identity
- C. a shared key
- D. an Azure Active Directory (Azure AD) user
Answer: B
Explanation:
Managed identity for Azure resources is a feature of Azure Active Directory. The feature provides Azure services with an automatically managed identity in Azure AD. You can use the Managed Identity capability to authenticate to any service that support Azure AD authentication.
Managed Identity authentication is required when your storage account is attached to a VNet.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/quickstart-bulk-load-copy-tsql-examples
NEW QUESTION # 60
You have two fact tables named Flight and Weather. Queries targeting the tables will be based on the join between the following columns.
You need to recommend a solution that maximizes query performance.
What should you include in the recommendation?
- A. In each table, create an identity column.
- B. In the tables use a hash distribution of ArrivalDateTime and ReportDateTime.
- C. In the tables use a hash distribution of ArrivaIAirportID and AirportlD.
- D. In each table, create a column as a composite of the other two columns in the table.
Answer: C
Explanation:
Hash-distribution improves query performance on large fact tables.
Incorrect Answers:
A: Do not use a date column for hash distribution. All data for the same date lands in the same distribution. If several users are all filtering on the same date, then only 1 of the 60 distributions do all the processing work.
NEW QUESTION # 61
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