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NEW QUESTION: 1
£100 of new cash is issued, which is then deposited in a bank which is part of a banking system operating a cash ratio of 10%. The maximum possible increase in the money supply which can follow from this transaction, additional to the initial deposit, is
A. £1000
B. £190
C. £900
D. £90
Answer: C
NEW QUESTION: 2
In an adequately powered, randomized controlled trial conducted over 3 years, a specific serious side
effect (i.e. reduction in leukocytes) with conventional therapy is seen in 0.5% of the study sample. In
patients who receive a newly discovered drug, only 0.45% experience the same side effect. Based on
these results, the minimum number of patients that would have to receive the new drug for 3 years to
statistically demonstrate the prevention of one episode of this side effect in at least one patient is:
A. 15.
B. 20.
C. 150.
D. 200.
E. 2000.
Answer: E
NEW QUESTION: 3
You have a new Azure Data Factory environment.
You need to periodically analyze pipeline executions from the last 60 days to identify trends in execution durations. The solution must use Azure Log Analytics to query the data and create charts.
Which diagnostic settings should you configure in Data Factory? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Log type: PipelineRuns
A pipeline run in Azure Data Factory defines an instance of a pipeline execution.
Storage location: An Azure Storage account
Data Factory stores pipeline-run data for only 45 days. Use Monitor if you want to keep that data for a longer time. With Monitor, you can route diagnostic logs for analysis. You can also keep them in a storage account so that you have factory information for your chosen duration.
Save your diagnostic logs to a storage account for auditing or manual inspection. You can use the diagnostic settings to specify the retention time in days.
References:
https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipeline-execution-triggers
https://docs.microsoft.com/en-us/azure/data-factory/monitor-using-azure-monitor