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NEW QUESTION: 1
A user's personal laptop was hacked. A technician troubleshooting the issue discovers the user used the numbers 123456789 as their account password. The user has not changed the password in two years.
Which of the following best practices should the technician recommend the user implement to prevent future hacking? (Select TWO).
A. Set login time restrictions
B. Change the password frequently
C. Use a more secure browser
D. Set a strong password
E. Configure screen saver
Answer: B,D
Explanation:
Section: Mix Questions

NEW QUESTION: 2
Azure Machine Learning Studioを使用して、大規模なデータストアからデータを取得しています。
システムクロックに基づいたランダムサンプリングシードを使用して、テスト目的でデータのサブセットを作成する必要があります。
パーティションとサンプルモジュールを実験に追加します。
モジュールのプロパティを選択する必要があります。
どの値を選択する必要がありますか?回答するには、回答エリアで適切なオプションを選択します。
注:それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation:
Box 1: Sampling
Create a sample of data
This option supports simple random sampling or stratified random sampling. This is useful if you want to create a smaller representative sample dataset for testing.
1. Add the Partition and Sample module to your experiment in Studio, and connect the dataset.
2. Partition or sample mode: Set this to Sampling.
3. Rate of sampling. See box 2 below.
Box 2: 0
3. Rate of sampling. Random seed for sampling: Optionally, type an integer to use as a seed value.
This option is important if you want the rows to be divided the same way every time. The default value is 0, meaning that a starting seed is generated based on the system clock. This can lead to slightly different results each time you run the experiment.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample

NEW QUESTION: 3
Note: This question is a part of a series of questions that present the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You have a Microsoft SQL Server database that contains the following tables.

The following columns contain data information:
* Date[Month] in the mmyyyy format
* Date[Date_ID] in the ddmmyyyy format
* Date[Date_name] in the mm/dd/yyyy format
* Monthly_returns[Month_ID] in the mmyyyy format
The Order table contains more than one million rows.
The Store table has relationship to the Monthly_returns table on the Store_ID column. This is the only relationship between the tables.
You plan to use Power BI desktop to create an analytics solution for the data.
End of repeated scenario.
You need to display the month as a three-letter abbreviation, followed by the year, such as jan2017.
You add a calculated column in Power BI.
Which DAX formula should you use for the calculated column? 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 bat between panes or scroll to view continent.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation
CONCATENATE
MMM
References: https://msdn.microsoft.com/en-us/library/ee634811.aspx

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