Data Engineering on Microsoft Azure

• #141

  You need to design an Azure Synapse Analytics dedicated SQL pool that meets the following 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?

  • Aas a temporal table.
  • Bas a SQL graph table.
  • Cas a degenerate dimension table.
  • Das a Type 2 slowly changing dimension (SCD) table.
  उत्तर दिखाएँ
• #142

  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?

  • AHash distribute the large fact tables in DW1 before performing the automated data loads.
  • BAssign a smaller resource class to the automated data load queries.
  • CAssign a larger resource class to the automated data load queries.
  • DCreate sampled statistics for every column in each table of DW1.
  उत्तर दिखाएँ
• #143

  You are designing a financial transactions table in an Azure Synapse Analytics dedicated SQL pool. The table will have a clustered columnstore index and will include the following columns: TransactionType: 40 million rows per transaction type CustomerSegment: 4 million per customer segment TransactionMonth: 65 million rows per month AccountType: 500 million per account type You 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 type You need to recommend a partition strategy for the table to minimize query times. On which column should you recommend partitioning the table?

  • ACustomerSegment.
  • BAccountType.
  • CTransactionType.
  • DTransactionMonth.
  उत्तर दिखाएँ
• #144

  You plan to use an Azure Data Lake Storage Gen2 account to implement a Data Lake development environment that meets the following requirements: Read and write access to data must be maintained if an availability zone becomes unavailable. Data that was last modified more than two years ago must be deleted automatically. Costs must be minimized. What should you configure?

  • AFor storage redundancy: Zone-redundant storage (ZRS). For data deletion: A lifecycle management policy.
  • BFor storage redundancy: Locally-redundant storage (LRS). For data deletion: A lifecycle management policy.
  • CFor storage redundancy: Zone-redundant storage (ZRS). For data deletion: Soft delete.
  • DFor storage redundancy: Geo-zone-redundant storage (GZRS). For data deletion: Versioning.
  उत्तर दिखाएँ
• #145

  You have the following Azure Data Factory pipelines ingest Data from System 1 Ingest Data from System2 Populate Dimensions Populate facts ingest Data from System1 and Ingest Data from System1 have no dependencies. Populate Dimensions must execute after Ingest Data from System1 and Ingest Data from System Populate Facts must execute after the Populate Dimensions pipeline. All the pipelines must execute every eight hours. What should you do to schedule the pipelines for execution?

  • AAdd an event trigger to all four pipelines.
  • BCreate a parent pipeline that contains the four pipelines and use an event trigger.
  • CCreate a parent pipeline that contains the four pipelines and use a schedule trigger.
  • DAdd a schedule trigger to all four pipelines.
  उत्तर दिखाएँ
• #146

  You have an Azure data factory named adf1 that contains a pipeline named ExecProduct. ExecProduct contains a data flow named Product. The Product data flow contains the following transformations: WeeklyData: A source that points to a CSV file in an Azure Data Lake Storage Gen2 account with 20 columns. ProductColumns: A select transformation that selects from WeeklyData six columns named ProductID, ProductDescr, ProductSubCategory, ProductCategory, ProductStatus, and ProductLastUpdated. ProductRows: An aggregate transformation. ProductList: A sink that outputs data to an Azure Synapse Analytics dedicated SQL pool. The Aggregate settings for ProductRows are configured as shown in the following exhibit. There will always be one output row for each unique value of ProductID.

  • AYes.
  • BNo.
  उत्तर दिखाएँ
• #147

  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 in container1 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: You use an Azure Synapse Analytics serverless SQL pool to create an external table that has an additional DateTime column. Does this meet the goal?

  • AYes.
  • BNo.
  उत्तर दिखाएँ
• #148

  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 monitoring experience in Data Factory. What should you add to each pipeline?

  • Aa resource tag
  • Ba correlation ID
  • Ca run group ID
  • Dan annotation
  उत्तर दिखाएँ
• #149

  You have an Azure Synapse Analytics pipeline named Pipeline1 that contains a data flow activity named Dataflow1. Pipeline1 retrieves files from an Azure Data Lake Storage Gen 2 account named storage1. Dataflow1 uses the AutoResolveIntegrationRuntime integration runtime configured with a core count of 128. You need to optimize the number of cores used by Dataflow1 to accommodate the size of the files in storage1. What should you configure?

  • ATo Pipeline1, add: A Get Metadata activity. For Dataflow1, set the core count by using: Dynamic content.
  • BTo Pipeline1, add: A Get Metadata activity. For Dataflow1, set the core count by using: User properties.
  • CTo Pipeline1, add: An if Condition activity. For Dataflow1, set the core count by using: Parameters.
  • DTo Pipeline1, add: A custom activity. For Dataflow1, set the core count by using: User properties.
  उत्तर दिखाएँ
• #150

  You have an Azure Synapse Analytics job that uses Scala. You need to view the status of the job. What should you do?

  • AFrom Azure Monitor, run a Kusto query against the AzureDiagnostics table.
  • BFrom Azure Monitor, run a Kusto query against the SparkLogying1 Event.CL table.
  • CFrom Synapse Studio, select the workspace. From Monitor, select Apache Sparks applications.
  • DFrom Synapse Studio, select the workspace. From Monitor, select SQL requests.
  उत्तर दिखाएँ
• #151

  You have an Azure subscription that contains the resources shown in the following table. You need to read the TSV files by using ad-hoc queries and the OPENROWSET function. The solution must assign a name and override the inferred data type of each column. What should you include in the OPENROWSET function?

  • Athe WITH clause.
  • Bthe ROWSET_OPTIONS bulk option.
  • Cthe DATAFILETYPE bulk option.
  • Dthe DATA_SOURCE parameter.
  उत्तर दिखाएँ
• #152

  You plan to ingest streaming social media data by using Azure Stream Analytics. The data will be stored in files in Azure Data Lake Storage, and then consumed by using Azure Datiabricks and PolyBase in Azure Synapse Analytics. You need to recommend a Stream Analytics data output format to ensure that the queries from Databricks and PolyBase against the files encounter the fewest possible errors. The solution must ensure that the tiles can be queried quickly and that the data type information is retained. What should you recommend?

  • AParquet.
  • BAvro.
  • CCSV.
  • DJSON.
  उत्तर दिखाएँ
• #1532 चुनें

  You have a SQL pool in Azure Synapse. A user reports that queries against the pool take longer than expected to complete. You need to add monitoring to the underlying storage to help diagnose the issue. Which two metrics should you monitor?

  • ACache used percentage.
  • BDWU Limit.
  • CSnapshot Storage Size.
  • DActive queries.
  • ECache hit percentage.
  उत्तर दिखाएँ
• #154

  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?

  • Aon-demand
  • Btumbling window
  • Cschedule
  • Devent
  उत्तर दिखाएँ
• #155

  Solution: You modify the files to ensure that each row is more than 1 MB. Does this meet the goal?

  • AYes.
  • BNo.
  उत्तर दिखाएँ
• #1562 चुनें

  You have an Azure Synapse Analytics dedicated SQL pool that contains a table named DimSalesPerson. DimSalesPerson contains the following columns: RepSourceI SalesRepID FirstName LastName StartDate EndDate Region You are developing an Azure Synapse Analytics pipeline that includes a mapping data flow named Dataflow1. Dataflow1 will read sales team data from an external source and use a Type 2 slowly changing dimension (SCD) when loading the data into DimSalesPerson. You need to update the last name of a salesperson in DimSalesPerson. Which two actions should you perform? Each correct answer presents part of the solution.

  • AUpdate three columns of an existing row.
  • BUpdate two columns of an existing row.
  • CInsert an extra row.
  • DUpdate one column of an existing row.
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• #157

  You are designing a statistical analysis solution that will use custom proprietary1 Python functions on near real-time data from Azure Event Hubs. You need to recommend which Azure service to use to perform the statistical analysis. The solution must minimize latency. What should you recommend?

  • AAzure Stream Analytics.
  • BAzure SQL Database.
  • CAzure Databricks.
  • DAzure Synapse Analytics.
  उत्तर दिखाएँ
• #158

  You are designing a folder structure for the files m an Azure Data Lake Storage Gen2 account. The account has one container that contains three years of data. You need to recommend a folder structure that meets the following requirements: Supports partition elimination for queries by Azure Synapse Analytics serverless SQL pooh Supports fast data retrieval for data from the current month Simplifies data security management by department Which folder structure should you recommend?

  • AYYYMMDDDepartmentDataSourceDataFile_YYYMMMDD.parquet
  • BDepdftmentDataSourceYYYMMDataFile_YYYYMMDD.parquet
  • CDDMMYYYYDepartmentDataSourceDataFile_DDMMYY.parquet
  • DDataSourceDepartmentYYYYMMDataFile_YYYYMMDD.parquet
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• #159

  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?

  • ASwitch the first partition from dbo.Sales to stg.Sales.
  • BSwitch the first partition from stg.Sales to dbo.Sales.
  • CUpdate dbo.Sales from stg.Sales.
  • DInsert the data from stg.Sales into dbo.Sales.
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• #1602 चुनें

  You use Azure Data Lake Storage Gen2. You need to ensure that workloads can use filter predicates and column projections to filter data at the time the data is read from disk. Which two actions should you perform?

  • AReregister the Microsoft Data Lake Store resource provider.
  • BReregister the Azure Storage resource provider.
  • CCreate a storage policy that is scoped to a container.
  • DRegister the query acceleration feature.
  • ECreate a storage policy that is scoped to a container prefix filter.
  उत्तर दिखाएँ

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