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NEW QUESTION: 1
Only the HR department in Germany should be able to access German employee data. However, the HR departments in other countries can currently access the German employee data. What are the possible reasons for this issue?
There are 2 correct answers to this question. Choose:
A. The Target Population is configured incorrectly.
B. The HR field for the German employees is incorrect.
C. The field permissions for Germany are incorrect.
D. The Permission Group is configured incorrectly.
Answer: A,D

NEW QUESTION: 2
As a Project Manager you are managing a project that has many requirements. The project is for one of your high profile customers, one who spends more than $5,000,000 a year with your company. To attain customer satisfaction, what must be met?
A. Completing the project on schedule and on budget
B. Completing products requirements
C. Completing the project's scope
D. Completing the project with the product having inherent characteristics that fulfill the requirements that it was to be built around
Answer: B

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.
You are analyzing a numerical dataset which contains missing values in several columns.
You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.
You need to analyze a full dataset to include all values.
Solution: Remove the entire column that contains the missing data point.
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Explanation
Use the Multiple Imputation by Chained Equations (MICE) method.
References:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3074241/
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data