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070-475 PDF DEMO:

QUESTION NO: 1
You have data generated by sensors. The data is sent to Microsoft Azure Event Hubs.
You need to have an aggregated view of the data in near real-time by using five minute tumbling windows to identity short-term trends. You must also have hourly and a daily aggregated views of the data.
Which technology should you use for each task? To answer, drag the appropriate technologies to the correct tasks. Each technology 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
Box 1: Azure HDInsight MapReduce
Azure Event Hubs allows you to process massive amounts of data from websites, apps, and devices.
The Event Hubs spout makes it easy to use Apache Storm on HDInsight to analyze this data in real time.
Box 2: Azure Event Hub
Box 3: Azure Stream Analytics
Stream Analytics is a new service that enables near real time complex event processing over streaming data.
Combining Stream Analytics with Azure Event Hubs enables near real time processing of millions of events per second. This enables you to do things such as augment stream data with reference data and output to storage (or even output to another Azure Event Hub for additional processing).

QUESTION NO: 2
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 states goals. Some question sets might have more than one correct solution, while the 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 implement a new data warehouse.
You have the following information regarding the data warehouse:
* The first data files for the data warehouse will be available in a few days.
* Most queries that will be executed against the data warehouse are ad-hoc.
* The schemas of data files that will be loaded to the data warehouse change often.
* One month after the planned implementation, the data warehouse will contain 15 TB of data.
You need to recommend a database solution to support the planned implementation.
Solution: You recommend an Apache Spark system.
Does this meet the goal?
A. No
B. Yes
Answer: A

QUESTION NO: 3
You have the following Hive query.
CREATE TABLE UserVisits (username string, urlvisited string, time date); LOAD DATA INPATH
'wasb:///Logs' OVERWRITE INTO TABLE UserVisits; Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the script.
NOTE: Each correct selection is worth one point.
Answer:
Explanation

QUESTION NO: 4
You plan to analyze the execution logs of a pipeline to identify failures by using Microsoft power BI.
You need to automate the collection of monitoring data for the planned analysis.
What should you do from Microsoft Azure?
A. Add a Log Profile
B. Create an Alert Rule Email
C. Save a Data Factory Log
D. Create a Data Factory Set
Answer: D
Explanation
You can import the results of a Log Analytics log search into a Power BI dataset so you can take advantage of its features such as combining data from different sources and sharing reports on the web and mobile devices.
To import data from a Log Analytics workspace into Power BI, you create a dataset in Power BI based on a log search query in Log Analytics. The query is run each time the dataset is refreshed. You can then build Power BI reports that use data from the dataset.
References: https://docs.microsoft.com/en-us/azure/azure-monitor/platform/powerbi

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