Data Engineering on Microsoft Azure

• #221

  You are designing an Azure Databricks cluster that runs user-defined local processes. You need 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 requirements Which cluster type should you recommend?

  • AStandard with Auto termination.
  • BStandard with Autoscaling.
  • CHigh Concurrency with Autoscaling.
  • DHigh Concurrency with Auto Termination.
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• #222

  You are planning a solution to aggregate streaming data that originates in Apache Kafka and is output to Azure Data Lake Storage Gen2. The developers who will implement the stream processing solution use Java, Which service should you recommend using to process the streaming data?

  • AAzure Data Factory.
  • BAzure Stream Analytics.
  • CAzure Databricks.
  • DAzure Event Hubs.
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• #223

  You configure version control for an Azure Data Factory instance as shown in the following exhibit.

  • AAzure Resource Manager (ARM) templates for the pipeline assets are stored in: adf_publish. A Data Factory Azure Resorce Manager (ARM) template named [contososales] can be found in: /.
  • BAzure Resource Manager (ARM) templates for the pipeline assets are stored in: /. A Data Factory Azure Resorce Manager (ARM) template named [contososales] can be found in: /dwh_batchetl/adf_publish/contososales.
  • CAzure Resource Manager (ARM) templates for the pipeline assets are stored in: main. A Data Factory Azure Resorce Manager (ARM) template named [contososales] can be found in: /contososales.
  • DAzure Resource Manager (ARM) templates for the pipeline assets are stored in: adf_publish. A Data Factory Azure Resorce Manager (ARM) template named [contososales] can be found in: /dwh_batchetl/adf_publish/contososales.
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• #224

  You have an Azure Data Lake Storage Gen2 account that contains a JSON file for customers. The file contains two attributes named FirstName and LastName. You need to copy the data from the JSON file to an Azure Synapse Analytics table by using Azure Databricks. A new column must be created that concatenates the FirstName and LastName values. You create the following components: A destination table in Azure Synapse An Azure Blob storage container A service principal Which five actions should you perform in sequence next in is Databricks notebook?

  • ABox 1: Read the file into a data frame. Box 2: Write the results to a table in Azure Synapse. Box 3: Write the results to a table in Azure Synapse. Box 4: Mount the Data Lake Storage onto DBFS. Box 5: Mount the Data Lake Storage onto DBFS.
  • BBox 1: Perform transformations on the data frame. Box 2: Write the results to a table in Azure Synapse. Box 3: Mount the Data Lake Storage onto DBFS. Box 4: Specify a temporary folder to stage the data. Box 5: Perform transformations on the data frame.
  • CBox 1: Mount the Data Lake Storage onto DBFS. Box 2: Read the file into a data frame. Box 3: Perform transformations on the data frame. Box 4: Specify a temporary folder to stage the data. Box 5: Write the results to a table in Azure Synapse.
  • DBox 1: Perform transformations on the data frame. Box 2: Read the file into a data frame. Box 3: Write the results to a table in Azure Synapse. Box 4: Specify a temporary folder to stage the data. Box 5: Mount the Data Lake Storage onto DBFS.
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• #225Pilih 2

  You are designing a star schema for a dataset that contains records of online orders. Each record includes an order date, an order due date, and an order ship date. You need to ensure that the design provides the fastest query times of the records when querying for arbitrary date ranges and aggregating by fiscal calendar attributes. Which two actions should you perform?

  • ACreate a date dimension table that has a DateTime key.
  • BUse built-in SQL functions to extract date attributes.
  • CCreate a date dimension table that has an integer key in the format of yyyymmdd.
  • DIn the fact table, use integer columns for the date fields.
  • EUse DateTime columns for the date fields.
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• #226

  You are building an Azure Analytics query that will receive input data from Azure IoT Hub and write the results to Azure Blob storage. You need to calculate the difference in readings per sensor per hour. How should you complete the query?

  • ABox 1: LAG. Box 2: OFFSET.
  • BBox 1: LAG. Box 2: LIMIT DURATION.
  • CBox 1: LAST. Box 2: OFFSET.
  • DBox 1: LEAD. Box 2: WHEN.
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• #227

  You have an Azure subscription that contains an Azure Synapse Analytics dedicated SQL pool named SQLPool1. SQLPool1 is currently paused. You need to restore the current state of SQLPool1 to a new SQL pool. What should you do first?

  • ACreate a workspace.
  • BCreate a user-defined restore point.
  • CResume SQLPool1.
  • DCreate a new SQL pool.
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• #228

  You have an Azure Synapse Analytics dedicated SQL pool. You need to Create a fact table named Table1 that will store sales data from the last three years. The solution must be optimized for the following query operations: Show order counts by week. Calculate sales totals by region. Calculate sales totals by product. Find all the orders from a given month. Which data should you use to partition Table1?

  • ARegion.
  • BProduct.
  • CWeek.
  • DMonth.
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• #229

  You have two Azure Blob Storage accounts named account1 and account2? You plan to create an Azure Data Factory pipeline that will use scheduled intervals to replicate newly created or modified blobs from account1 to account? You need to recommend a solution to implement the pipeline. The solution must meet the following requirements: Ensure that the pipeline only copies blobs that were created of modified since the most recent replication event. Minimize the effort to create the pipeline. What should you recommend?

  • ACreate a pipeline that contains a flowlet.
  • BCreate a pipeline that contains a Data Flow activity.
  • CRun the Copy Data tool and select Metadata-driven copy task.
  • DRun the Copy Data tool and select Built-in copy task.
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• #230

  You are implementing a batch dataset in the Parquet format. Data tiles will be produced by using Azure Data Factory and stored in Azure Data Lake Storage Gen2. The files will be consumed by an Azure Synapse Analytics serverless SQL pool. You need to minimize storage costs for the solution. What should you do?

  • AStore all the data as strings in the Parquet tiles.
  • BUse OPENROWEST to query the Parquet files.
  • CCreate an external table mat contains a subset of columns from the Parquet files.
  • DUse Snappy compression for the files.
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• #231

  You are designing an Azure Data Lake Storage solution that will transform raw JSON files for use in an analytical workload. You need to recommend a format for the transformed files. The solution must meet the following requirements: Contain information about the data types of each column in the files. Support querying a subset of columns in the files. Support read-heavy analytical workloads. Minimize the file size. What should you recommend?

  • AJSON.
  • BCSV.
  • CApache Avro.
  • DApache Parquet.
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• #232

  You are designing a highly available Azure Data Lake Storage solution that will induce geo-zone-redundant storage (GZRS). You need to monitor for replication delays that can affect the recovery point objective (RPO). What should you include in the monitoring solution?

  • ALast Sync Time.
  • BAverage Success E2E Latency.
  • C5xx: Server Error errors
  • DAvailability.
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• #233

  You are designing a sales transactions table in an Azure Synapse Analytics dedicated SQL pool. The table will contains approximately 60 million rows per month and will be partitioned by month. The table will use a clustered column store index and round-robin distribution. Approximately how many rows will there be for each combination of distribution and partition?

  • A1 million.
  • B5 million.
  • C20 million.
  • D60 million.
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• #234

  Solution: You copy the files to a table that has a columnstore index.

  • AYes.
  • BNo.
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• #235

  You have an Azure subscription that contains an Azure Data Lake Storage account. The storage account contains a data lake named DataLake1. You plan to use an Azure data factory to ingest data from a folder in DataLake1, transform the data, and land the data in another folder. You need to ensure that the data factory can read and write data from any folder in the DataLake1 file system. The solution must meet the following requirements: Minimize the risk of unauthorized user access. Use the principle of least privilege. Minimize maintenance effort. How should you configure access to the storage account for the data factory?

  • AUse: a Shared Access Signature (SAS). to authenticate by using: a stored access policy.
  • BUse: Microsoft Azure Active Directory (Azure AD), part of Microsoft Entra. to authenticate by using: a managed identity.
  • CUse: a shared key. to authenticate by using: an Authorization header.
  • DUse: a Shared Access Signature (SAS). to authenticate by using: an Authorization header.
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• #236Pilih 2

  You have an Azure Stream Analytics query. The query returns a result set that contains 10,000 distinct values for a column named clusterID. You monitor the Stream Analytics job and discover high latency. You need to reduce the latency. Which two actions should you perform? Each correct answer presents a complete solution.

  • AAdd a pass-through query.
  • BAdd a temporal analytic function.
  • CScale out the query by using PARTITION BY.
  • DConvert the query to a reference query.
  • EIncrease the number of streaming units.
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• #237

  You are designing an enterprise data warehouse in Azure Synapse Analytics that will store website traffic analytics in a star schema. You plan to have a fact table for website visits. The table will be approximately 5 GB. You need to recommend which distribution type and index type to use for the table. The solution must provide the fastest query performance. What should you recommend?

  • ADistribution: Round robin. Index: Clustered columnstore.
  • BDistribution: Replicated. Index: Nonclustered.
  • CDistribution: Hash. Index: Clustered columnstore.
  • DDistribution: Hash. Index: Clustered.
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• #238Pilih 2

  You need to implement a Type 3 slowly changing dimension (SCD) for product category data in an Azure Synapse Analytics dedicated SQL pool. You have a table that was created by using the following Transact-SQL statement. Which two columns should you add to the table?

  • A[EffectiveStartDate] [datetime] NOT NULL,.
  • B[CurrentProductCategory] [nvarchar] (100) NOT NULL,.
  • C[EffectiveEndDate] [datetime] NULL,.
  • D[ProductCategory] [nvarchar] (100) NOT NULL,.
  • E[OriginalProductCategory] [nvarchar] (100) NOT NULL,.
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• #239

  You have an Azure Synapse Analytics dedicated SQL pool named Pool1 and a database named 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?

  • AConnect to the built-in pool and run dbcc pdw_showspaceused.
  • BConnect to the built-in pool and run dbcc checkalloc.
  • CConnect to Pool1 and query sys.dm_pdw_node_scacus.
  • DConnect to Pool1 and query sys.dm_pdw_nodes_db_partition_scacs.
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• #240

  You have an Azure Synapse workspace named MyWorkspace that contains an Apache Spark database named mytestdb. You run the following command in an Azure Synapse Analytics Spark pool in MyWorkspace. CREATE TABLE mytestdb.myParquetTable( EmployeeID int, EmployeeName string, EmployeeStartDate date) USING Parquet You then use Spark to insert a row into mytestdb.myParquetTable. The row contains the following data. One minute later, you execute the following query from a serverless SQL pool in MyWorkspace. SELECT EmployeeID FROM mytestdb.dbo.myParquetTable WHERE name = 'Alice'; What will be returned by the query?

  • A24.
  • Ban error.
  • Ca null value.
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