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NEW QUESTION: 1
Use the following login credentials as needed:
Azure Username: xxxxx
Azure Password: xxxxx
The following information is for technical support purposes only:
Lab Instance: 10277521
You plan to create multiple pipelines in a new Azure Data Factory V2.
You need to create the data factory, and then create a scheduled trigger for the planned pipelines. The trigger must execute every two hours starting at 24:00:00.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
Step 1: Create a new Azure Data Factory V2
1. Go to the Azure portal.
2. Select Create a resource on the left menu, select Analytics, and then select Data Factory.
4. On the New data factory page, enter a name.
5. For Subscription, select your Azure subscription in which you want to create the data factory.
6. For Resource Group, use one of the following steps:
Select Use existing, and select an existing resource group from the list.
Select Create new, and enter the name of a resource group.
7. For Version, select V2.
8. For Location, select the location for the data factory.
9. Select Create.
10. After the creation is complete, you see the Data Factory page.
Step 2: Create a schedule trigger for the Data Factory
1. Select the Data Factory you created, and switch to the Edit tab.
2. Click Trigger on the menu, and click New/Edit.
3. In the Add Triggers page, click Choose trigger..., and click New.
4. In the New Trigger page, do the following steps:
a. Confirm that Schedule is selected for Type.
b. Specify the start datetime of the trigger for Start Date (UTC) to: 24:00:00 c. Specify Recurrence for the trigger. Select Every Hour, and enter 2 in the text box.
5. In the New Trigger window, check the Activated option, and click Next.
6. In the New Trigger page, review the warning message, and click Finish.
7. Click Publish to publish changes to Data Factory. Until you publish changes to Data Factory, the trigger does not start triggering the pipeline runs.
References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-schedule-trigger
NEW QUESTION: 2
DLPe application strategies, in order of decreasing security, are:
A. Editor, Explorer, Trusted, Archiver
B. Editor, Explorer, Archiver, Trusted
C. Secure, Trusted, Editor, Allow
D. Trusted, Explorer, Editor, Archiver
Answer: A
NEW QUESTION: 3
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 stated goals. Some question sets might have more than one correct solution, while 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.
Your company has multiple databases that contain millions of sales transactions.
You plan to implement a data mining solution to identity purchasing fraud.
You need to design a solution that mines 10 terabytes (TB) of sales data. The solution must meet the following requirements:
* Run the analysis to identify fraud once per week.
* Continue to receive new sales transactions while the analysis runs.
* Be able to stop computing services when the analysis is NOT running.
Solution: You create a Cloudera Hadoop cluster on Microsoft Azure virtual machines.
Does this meet the goal?
A. Yes
B. No
Answer: A
Explanation:
Explanation: Processing large amounts of unstructured data requires serious computing power and also maintenance effort. As load on computing power typically fluctuates due to time and seasonal influences and/or processes running on certain times, a cloud solution like Microsoft Azure is a good option to be able to scale up easily and pay only for what is actually used.