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NEW QUESTION: 1
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、述べられた目標を達成する可能性のある独自の解決策が含まれています。一部の質問セットには複数の正しい解決策がある場合がありますが、他の質問セットには正しい解決策がない場合があります。
このシナリオで質問に回答した後は、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
値としてSalaryという名前のメジャーと、軸としてEmployeeという名前のフィールドを含むクラスター化された棒グラフがあります。給与は、米ドルを表す数値としてデータに表示されます。
どの従業員が給与の中央値を上回っているかを示す参照線を作成する必要があります。
解決策：定数線を作成し、値を.5に設定します。
これは目標を達成していますか？
A. はい
B. いいえ
Answer: B
Explanation:
Explanation
Instead create a percentile line by using the Salary measure and set the percentile to 50%.
Note: The 50th percentile is also known as the median or middle value where 50 percent of observations fall below.
Reference:
https://dash-intel.com/powerbi/statistical_functions_percentile.php
NEW QUESTION: 2
DNSリゾルバーからDNSサーバーに送信されるクエリの種類は何ですか？
A. Simple
B. Type Q query
C. Recursive
D. Iterative
Answer: C
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, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have Azure IoT Edge devices that generate streaming data.
On the devices, you need to detect anomalies in the data by using Azure Machine Learning models.
Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.
Solution: You deploy Azure Stream Analytics as an IoT Edge module.
Does this meet the goal?
A. Yes
B. No
Answer: A
Explanation:
Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies:
temporary and persistent.
Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly- detection
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