Which windowing function should you use to perform the streaming aggregation of the sales data?

• A.Sliding
• B.Hopping
• C.Session
• D.Tumbling

Correct Answer: D

Section: [none]
Explanation:
Scenario: The sales data, including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytics process will perform aggregations that must be done continuously, without gaps, and without overlapping.
Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.

Reference:
https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/stream-analytics/stream-analytics-window- functions.md

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You have an Azure Synapse Analytics dedicated SQL pool named Pool1 and a database named DB1. DB1 contains a fact table named Table.
You need to identify the extent of the data skew in Table1.
What should you do in Synapse Studio?

• A.Connect to Pool1 and query sys.dm_pdw_nodes_db_partition_stats.
• B.Connect to the built-in pool and run DBCC CHECKALLOC.
• C.Connect to Pool1 and run DBCC CHECKALLOC.
• D.Connect to the built-in pool and query sys.dm_pdw_nodes_db_partition_stats.

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You have 10 Azure virtual machines that have SQL Server installed.
You need to implement a backup strategy to ensure that you can restore specific databases to other SQL
Server instances. The solution must provide centralized management of the backups.
What should you include in the backup strategy?

• A.Automated Backup in the SQL virtual machine settings
• B.Azure Backup
• C.Azure Site Recovery
• D.SQL Server Agent jobs

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