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  1. Home
  2. Microsoft Certification
  3. DP-203 Exam
  4. Microsoft.DP-203.v2023-08-29.q209 Dumps
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Question 131

You have an Azure Data Factory pipeline that is triggered hourly.
The pipeline has had 100% success for the past seven days.
The pipeline execution fails, and two retries that occur 15 minutes apart also fail. The third failure returns the following error.

What is a possible cause of the error?

Correct Answer: A
insert code

Question 132

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.

Correct Answer:

Explanation
Graphical user interface, application, table Description automatically generated

Box 1: {date}/product.csv
In the 2nd exhibit we see: Location: refdata / 2020-03-20
Note: Path Pattern: This is a required property that is used to locate your blobs within the specified container.
Within the path, you may choose to specify one or more instances of the following 2 variables:
{date}, {time}
Example 1: products/{date}/{time}/product-list.csv
Example 2: products/{date}/product-list.csv
Example 3: product-list.csv
Box 2: YYYY-MM-DD
Note: Date Format [optional]: If you have used {date} within the Path Pattern that you specified, then you can select the date format in which your blobs are organized from the drop-down of supported formats.
Example: YYYY/MM/DD, MM/DD/YYYY, etc.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-use-reference-data
insert code

Question 133

You plan to create an Azure Data Factory pipeline that will include a mapping data flow.
You have JSON data containing objects that have nested arrays.
You need to transform the JSON-formatted data into a tabular dataset. The dataset must have one tow for each item in the arrays.
Which transformation method should you use in the mapping data flow?

Correct Answer: B
Explanation
Use the flatten transformation to take array values inside hierarchical structures such as JSON and unroll them into individual rows. This process is known as denormalization.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/data-flow-flatten
insert code

Question 134

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?

Correct Answer: C
A High Concurrency cluster is a managed cloud resource. The key benefits of High Concurrency clusters are that they provide fine-grained sharing for maximum resource utilization and minimum query latencies.
Databricks chooses the appropriate number of workers required to run your job. This is referred to as autoscaling. Autoscaling makes it easier to achieve high cluster utilization, because you don't need to provision the cluster to match a workload.
Reference:
https://docs.microsoft.com/en-us/azure/databricks/clusters/configure
insert code

Question 135

You are creating dimensions for a data warehouse in an Azure Synapse Analytics dedicated SQL pool.
You create a table by using the Transact-SQL statement shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation

Box 1: Type 2
A Type 2 SCD supports versioning of dimension members. Often the source system doesn't store versions, so the data warehouse load process detects and manages changes in a dimension table. In this case, the dimension table must use a surrogate key to provide a unique reference to a version of the dimension member. It also includes columns that define the date range validity of the version (for example, StartDate and EndDate) and possibly a flag column (for example, IsCurrent) to easily filter by current dimension members.
Reference:
https://docs.microsoft.com/en-us/learn/modules/populate-slowly-changing-dimensions-azure-synapse-analytics-p
insert code
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