また、NewValidDumpsのMicrosoftの070-475試験復習赤本試験トレーニング資料が信頼できるのは多くの受験生に証明されたものです。NewValidDumpsのMicrosoftの070-475試験復習赤本試験トレーニング資料を利用したらきっと成功できますから、NewValidDumpsを選ばない理由はないです。試験の準備をするためにNewValidDumpsのMicrosoftの070-475試験復習赤本試験トレーニング資料を買うのは冒険的行為と思ったとしたら、あなたの人生の全てが冒険なことになります。 これもNewValidDumpsが実力を体現する点です。我々の試験トレーニング資料はあなたが買いてから友達に勧めなければならない魅力を持っています。 真剣にNewValidDumpsのMicrosoft 070-475試験復習赤本問題集を勉強する限り、受験したい試験に楽に合格することができるということです。

Microsoft Azure 070-475 まだ何を待っていますか。

Microsoft Azure 070-475試験復習赤本 - Design and Implement Big Data Analytics Solutions これは多くの受験生たちによって証明されたことです。 それは正確性が高くて、カバー率も広いです。あなたはNewValidDumpsの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。

例えば070-475試験復習赤本認定試験などです。その中の試験、どちらを受験しましたか。もし一つの認証資格を持っていないなら、IT認定試験を申し込んで試験の資格を取得する必要があります。

Microsoft 070-475試験復習赤本 - 我々はあなたに試験に安心させます。

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070-475 PDF DEMO:

QUESTION NO: 1
You need to create a query that identifies the trending topics.
How should you complete the query? 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.
Answer:
Explanation
From scenario: Topics are considered to be trending if they generate many mentions in a specific country during a 15-minute time frame.
Box 1: TimeStamp
Azure Stream Analytics (ASA) is a cloud service that enables real-time processing over streams of data flowing in from devices, sensors, websites and other live systems. The stream-processing logic in ASA is expressed in a SQL-like query language with some added extensions such as windowing for performing temporal calculations.
ASA is a temporal system, so every event that flows through it has a timestamp. A timestamp is assigned automatically based on the event's arrival time to the input source but you can also access a timestamp in your event payload explicitly using TIMESTAMP BY:
SELECT * FROM SensorReadings TIMESTAMP BY time
Box 2: GROUP BY
Example: Generate an output event if the temperature is above 75 for a total of 5 seconds SELECT sensorId, MIN(temp) as temp FROM SensorReadings TIMESTAMP BY time GROUP BY sensorId,
SlidingWindow(second, 5) HAVING MIN(temp) > 75 Box 3: SlidingWindow Windowing is a core requirement for stream processing applications to perform set-based operations like counts or aggregations over events that arrive within a specified period of time. ASA supports three types of windows: Tumbling, Hopping, and Sliding.
With a Sliding Window, the system is asked to logically consider all possible windows of a given length and output events for cases when the content of the window actually changes - that is, when an event entered or existed the window.

QUESTION NO: 2
You need to automate the creation of a new Microsoft Azure data factory.
What are three possible technologies that you can use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point
A. the SOAP service
B. the Microsoft .NET framework class library
C. T-SQL statements
D. Azure PowerShell cmdlets
E. the REST API
Answer: B,D,E
Explanation
https://docs.microsoft.com/en-us/azure/data-factory/data-factory-introduction

QUESTION NO: 3
You have an Apache Hive cluster in Microsoft Azure HDInsight. The cluster contains 10 million data files.
You plan to archive the data.
The data will be analyzed monthly.
You need to recommend a solution to move and store the data. The solution must minimize how long it takes to move the data and must minimize costs.
Which two services should you include in the recommendation? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Azure Data Factory
B. Azure Data Lake
C. Azure Table Storage
D. Microsoft SQL Server Integration Services (SSIS)
E. Azure Queue storage
Answer: A,B
Explanation
D: To analyze data in HDInsight cluster, you can store the data either in Azure Storage, Azure Data
Lake Storage Gen 1/Azure Data Lake Storage Gen 2, or both. Both storage options enable you to safely delete HDInsight clusters that are used for computation without losing user data.
E: The Spark activity in a Data Factory pipeline executes a Spark program on your own or on-demand
HDInsight cluster. It handles data transformation and the supported transformation activities.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-use-data-lake-store
https://docs.microsoft.com/en-us/azure/data-factory/transform-data-using-spark

QUESTION NO: 4
You are designing an application that will perform real-time processing by using Microsoft
Azure Stream Analytics.
You need to identify the valid outputs of a Stream Analytics job.
What are three possible outputs that you can use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. a Hive table in Azure HDInsight
B. Azure SQL Database
C. Microsoft Power BI
D. Azure Blob storage
E. Azure Redis Cache
Answer: B,C,D
Explanation
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-outputs

QUESTION NO: 5
You use Microsoft Azure Data Factory to orchestrate data movements and data transformations within Azure.
You plan to monitor the data factory to ensure that all of the activity slices run successfully. You need to identify a solution to rerun failed slices. What should you do?
A. Move the data factory to a different resource group.
B. Delete and recreate the data factory.
C. From the Azure portal, select the Data slice blade, and then click Run.
D. From the Diagram tile on the Data Factory blade of the Azure portal, double-click the pipeline that has a failed slice.
Answer: A

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Updated: May 27, 2022