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  1. Home
  2. Microsoft Certification
  3. DP-203 Exam
  4. Microsoft.DP-203.v2023-01-01.q218 Dumps
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Question 86

You have the following table named Employees.

You need to calculate the employee_type value based on the hire_date value.
How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Correct Answer:

Reference:
https://docs.microsoft.com/en-us/sql/t-sql/language-elements/case-transact-sql
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Question 87

You have an Azure Storage account and a data warehouse in Azure Synapse Analytics in the UK South region.
You need to copy blob data from the storage account to the data warehouse by using Azure Data Factory. The solution must meet the following requirements:
Ensure that the data remains in the UK South region at all times.
Minimize administrative effort.
Which type of integration runtime should you use?

Correct Answer: A

Reference:
https://docs.microsoft.com/en-us/azure/data-factory/concepts-integration-runtime
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Question 88

You are designing a fact table named FactPurchase in an Azure Synapse Analytics dedicated SQL pool. The table contains purchases from suppliers for a retail store. FactPurchase will contain the following columns.

FactPurchase will have 1 million rows of data added daily and will contain three years of data.
Transact-SQL queries similar to the following query will be executed daily.
SELECT
SupplierKey, StockItemKey, COUNT(*)
FROM FactPurchase
WHERE DateKey >= 20210101
AND DateKey <= 20210131
GROUP By SupplierKey, StockItemKey
Which table distribution will minimize query times?

Correct Answer: B
Hash-distributed tables improve query performance on large fact tables, and are the focus of this article.
Round-robin tables are useful for improving loading speed.
Incorrect:
Not D: Do not use a date column. . All data for the same date lands in the same distribution. If several users are all filtering on the same date, then only 1 of the 60 distributions do all the processing work.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables- distribute
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Question 89

You have an Azure Data Lake Storage Gen2 container.
Data is ingested into the container, and then transformed by a data integration application. The data is NOT modified after that. Users can read files in the container but cannot modify the files.
You need to design a data archiving solution that meets the following requirements:
New data is accessed frequently and must be available as quickly as possible.
Data that is older than five years is accessed infrequently but must be available within one second when requested.
Data that is older than seven years is NOT accessed. After seven years, the data must be persisted at the lowest cost possible.
Costs must be minimized while maintaining the required availability.
How should you manage the data? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point

Correct Answer:

Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers
https://azure.microsoft.com/en-us/updates/reduce-data-movement-and-make-your-queries-more-efficient-with-the-general-availability-of-replicated-tables/
https://azure.microsoft.com/en-us/blog/replicated-tables-now-generally-available-in-azure-sql-data-warehouse/
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Question 90

You plan to develop a dataset named Purchases by using Azure databricks Purchases will contain the following columns:
* ProductID
* ItemPrice
* lineTotal
* Quantity
* StorelD
* Minute
* Month
* Hour
* Year
* Day
You need to store the data to support hourly incremental load pipelines that will vary for each StoreID. the solution must minimize storage costs. How should you complete the rode? To answer, select the appropriate options In the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation

Box 1: partitionBy
We should overwrite at the partition level.
Example:
df.write.partitionBy("y","m","d")
mode(SaveMode.Append)
parquet("/data/hive/warehouse/db_name.db/" + tableName)
Box 2: ("StoreID", "Year", "Month", "Day", "Hour", "StoreID")
Box 3: parquet("/Purchases")
Reference:
https://intellipaat.com/community/11744/how-to-partition-and-write-dataframe-in-spark-without-deleting-partitio
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