Practice Free DP-203 Exam Online Questions

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.

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You are designing an Azure Stream Analytics solution that will analyze Twitter data.

You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once.

Solution: You use a hopping window that uses a hop size of 5 seconds and a window size 10 seconds.

Does this meet the goal?

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You have an Azure Databricks workspace named workspace1 in the Standard pricing tier.

You need to configure workspace1 to support autoscaling all-purpose clusters.

The solution must meet the following requirements:

✑ Automatically scale down workers when the cluster is underutilized for three minutes.

✑ Minimize the time it takes to scale to the maximum number of workers.

✑ Minimize costs.

What should you do first?

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You have an Azure data factory.

You need to examine the pipeline failures from the last 180 flays.

What should you use?

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HOTSPOT

You have a Microsoft SQL Server database that uses a third normal form schema.

You plan to migrate the data in the database to a star schema in an Azure Synapse Analytics dedicated SQI pool.

You need to design the dimension tables. The solution must optimize read operations.

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.

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Correct Answer:

Explanation:

Box 1: Denormalize to a second normal form

Denormalization is the process of transforming higher normal forms to lower normal forms via storing the join of higher normal form relations as a base relation. Denormalization increases the performance in data retrieval at cost of bringing update anomalies to a database.

Box 2: New identity columns

The collapsing relations strategy can be used in this step to collapse classification entities into component entities to obtain flat dimension tables with single-part keys that connect directly to the fact table. The single-part key is a surrogate key generated to ensure it remains unique over time.

Example:

Note: 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://www.mssqltips.com/sqlservertip/5614/explore-the-role-of-normal-forms-in-dimensional-modeling/

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-identity

You have an Azure subscription that contains the resources shown in the following table.

Diagnostic logs from ADF1 are sent to LA1. ADF1 contains a pipeline named Pipeline that copies data (torn DB1 to Dw1.

You need to perform the following actions:

• Create an action group named AG1.

• Configure an alert in ADF1 to use AG1.

In which resource group should you create AG1?

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You plan to build a structured streaming solution in Azure Databricks. The solution will count new events in five-minute intervals and report only events that arrive during the interval. The output will be sent to a Delta Lake table.

Which output mode should you use?

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You have an Azure Data Lake Storage account that has a virtual network service endpoint configured.

You plan to use Azure Data Factory to extract data from the Data Lake Storage account. The data will then be loaded to a data warehouse in Azure Synapse Analytics by using PolyBase.

Which authentication method should you use to access Data Lake Storage?

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HOTSPOT

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.

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Correct Answer:

Explanation:

Box 1: Incremental load

Box 2: Tumbling window

Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time intervals. The following diagram illustrates a stream with a series of events and how they are mapped into 10-second tumbling windows.

Reference: https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics

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?

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HOTSPOT

You have an Azure Synapse serverless SQL pool.

You need to read JSON documents from a file by using the OPENROWSET function.

How should you complete the query? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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Correct Answer: