A recurring event is being stored in two databases that are housed in different geographical
locations. A data analyst notices the event is being logged three hours earlier in one database than in
the other database. Which of the following is the MOST likely cause of the issue?
Correct Answer: C
Explanation:
The most likely cause of the issue is that the databases are recording the event in different time
zones. For example, if one database is in New York and the other database is in Los Angeles, there is
a three-hour difference between them. Therefore, an event that occurs at 12:00 PM in New York
would be recorded as 9:00 AM in Los Angeles. To avoid this issue, the databases should either use a
common time zone or convert the timestamps to a standard format. Therefore, option C is correct.
Option A is incorrect because the data analyst is not querying the databases incorrectly, but rather
observing a discrepancy in the timestamps.
Option B is incorrect because the databases are recording the same event, but with different
timestamps.
Option D is incorrect because the second database is not logging incorrectly, but rather using a
different time zone.
Question 2
Five dogs have the following heights in millimeters:
300, 430, 170, 470, 600
Which of the following is the mean height for the five dogs?
Correct Answer: A
Explanation:
The mean height for the five dogs is calculated by adding up all the heights and dividing by the
number of dogs. The formula is:
mean = (300 + 430 + 170 + 470 + 600) / 5 mean = 1970 / 5 mean = 394
Therefore, option A is correct.
Option B is incorrect because it is the median height, which is the middle value when the heights are
arranged in ascending order.
Option C is incorrect because it is the mean height multiplied by 1.25.
Option D is incorrect because it is the mean height multiplied by 1.28.
Question 3
Which of the following is a common data analytics tool that is also used as an interpreted, high-level,
general-purpose programming language?
Correct Answer: D
Explanation:
Python is a common data analytics tool that is also used as an interpreted, high-level, general purpose programming language. Python has a simple and expressive syntax that makes it easy to
read and write code. Python also has a rich set of libraries and frameworks that support various tasks
and applications in data analytics, such as data manipulation, visualization, machine learning, natural
language processing, web scraping, and more. Some examples of popular Python libraries for data
analytics are pandas, numpy, matplotlib, seaborn, scikit-learn, nltk, and beautiful soup. Python is
different from other data analytics tools that are not programming languages but rather software
applications or platforms that provide graphical user interfaces (GUIs) for data analysis and
visualization. Some examples of these tools are SAS, Microsoft Power BI, IBM SPSS. Therefore, the
correct answer is D. Reference: [What is Python? | Definition and Examples], [Python Libraries for
Data Science]
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