DP-203 Exam Dumps – Our Features

You have an Azure Synapse Analytics Apache Spark pool named Pool1.You plan to load JSON files from an Azure Data Lake Storage Gen2 container into the tables in Pool1. The structure and data types vary by file.You need to load the files into the tables. The solution must maintain the source data types.What should you do?

• Use a Get Metadata activity in Azure Data Factory.
• Use a Conditional Split transformation in an Azure Synapse data flow.
• Load the data by using the OPEHROwset Transact-SQL command in an Azure Synapse Anarytics serverless SQL pool.
• Load the data by using PySpark.

You are designing a dimension table in an Azure Synapse Analytics dedicated SQL pool.You need to create a surrogate key for the table. The solution must provide the fastest query performance.What should you use for the surrogate key?

• a GUID column
• a sequence object
• an IDENTITY column

You create an Azure Databricks cluster and specify an additional library to install.When you attempt to load the library to a notebook, the library in not found.You need to identify the cause of the issue.What should you review?

• notebook logs
• cluster event logs
• global init scripts logs
• workspace logs

You have an Azure Synapse Analytics dedicated SQL Pool1. Pool1 contains a partitioned fact table named dbo.Sales and a staging table named stg.Sales that has the matching table and partition definitions.You need to overwrite the content of the first partition in dbo.Sales with the content of the same partition in stg.Sales. The solution must minimize load times.What should you do?

• Switch the first partition from dbo.Sales to stg.Sales.
• Switch the first partition from stg.Sales to dbo. Sales.
• Update dbo.Sales from stg.Sales.
• Insert the data from stg.Sales into dbo.Sales.

You plan to create a dimension table in Azure Synapse Analytics that will be less than 1 GB.You need to create the table to meet the following requirements:* Provide the fastest Query time.* Minimize data movement during queries.Which type of table should you use?

• hash distributed
• heap
• replicated
• round-robin

A company purchases IoT devices to monitor manufacturing machinery. The company uses an Azure IoTHub to communicate with the IoT devices.The company must be able to monitor the devices in real-time.You need to design the solution.What should you recommend?

• Azure Stream Analytics Edge application using Microsoft Visual Studio.
• Azure Analytics Services using Azure portal
• Azure Analysis Services using Microsoft visual Studio
• Azure Data Factory instance using Microsoft visual Studio

You have an Azure Synapse Analytics dedicated SQL pool that contains a table named Table1.You have files that are ingested and loaded into an Azure Data Lake Storage Gen2 container named container1.You plan to insert data from the files into Table1 and azure Data Lake Storage Gen2 container named container1.You plan to insert data from the files into Table1 and transform the data. Each row of data in 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 DateTime is stored as an additional column in Table1.Solution: In an Azure Synapse Analytics pipeline, you use a Get Metadata activity that retrieves the DateTime of the files.Does this meet the goal?

• Yes
• No

You develop data engineering solutions for a company.A project requires the deployment of data to Azure Data Lake Storage.You need to implement role-based access control (RBAC) so that project members can manage the Azure Data Lake Storage resources.Which three actions should you perform? Each correct answer presents part of the solution.NOTE: Each correct selection is worth one point.

• Assign Azure AD security groups to Azure Data Lake Storage.
• Configure end-user authentication for the Azure Data Lake Storage account.
• Configure service-to-service authentication for the Azure Data Lake Storage account.
• Create security groups in Azure Active Directory (Azure AD) and add project members.
• Configure access control lists (ACL) for the Azure Data Lake Storage account.

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 stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.You plan to create an Azure Databricks workspace that has a tiered structure. The workspace 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 for Databricks environments:The data engineers must share a cluster.The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.You need to create the Databricks clusters for the workloads.Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a High Concurrency cluster for the jobs.Does this meet the goal?

• Yes
• No

You are designing an Azure Databricks table. The table will ingest an average of 20 million streaming events per day.You need to persist the events in the table for use in incremental load pipeline jobs in Azure Databricks. The solution must minimize storage costs and incremental load times.What should you include in the solution?

• Partition by DateTime fields.
• Sink to Azure Queue storage.
• Include a watermark column.
• Use a JSON format for physical data storage.