An analyst has been tracking company intranet usage and has been asked to create a chat to show
the most-used/most-clicked portions of a homepage that contains more than 30 links. Which of the
following visualizations would BEST illustrate this information?
A.
Scatter plot
B.
Heat map
C.
Pie chart
D.
Infographic
Correct Answer: B
Explanation:
This is because a heat map is a visualization that uses colors to represent different values or
intensities of a variable. A heat map can be used to show the most-used/most-clicked portions of a
homepage that contains more than 30 links by assigning different colors to each link based on how
frequently they are clicked by the users. For example, a link that is clicked very often can be colored
red, while a link that is clicked rarely can be colored blue. A heat map can help the analyst to identify
which links are more popular or important than others on the homepage. The other visualizations
are not as effective as a heat map for this purpose. Here is why:
A scatter plot is a visualization that uses dots or points to represent the relationship between two
variables. A scatter plot cannot show the most-used/most-clicked portions of a homepage that
contain more than 30 links because it does not have a clear way of mapping each link to a point on
the graph.
A pie chart is a visualization that uses slices or sectors to represent the proportion of each category in
a whole. A pie chart cannot show the most-used/most-clicked portions of a homepage that contains
more than 30 links because it does not have enough space to display all the categories clearly and
accurately.
An infographic is a visualization that uses images, icons, charts, and text to convey information or tell
a story. An infographic cannot show the most-used/most-clicked portions of a homepage that contain
more than 30 links because it does not have a consistent or standardized way of representing each
link and its click frequency.
Question #2 (Topic: Demo Questions)
Which of the following would be the BEST technique for the analyst to apply to acquire the data?
A.
Web scraping
B.
Sampling
C.
Data wrangling
D.
ETL
Correct Answer: A
Explanation:
This is because web scraping is a technique that allows the analyst to extract data from web pages,
such as articles from a digital news outlet. Web scraping can be done using various tools and
methods, such as Python libraries, browser extensions, or online services. The other techniques are
notsuitable for acquiring data from web pages. Here is why:
Sampling is a technique that involves selecting a subset of data from a larger population, usually for
statistical analysis or testing purposes. Sampling does not help the analyst to acquire data from web
pages, but rather to reduce the amount of data to be analyzed.
Data wrangling is a technique that involves transforming and cleaning data to make it suitable for
analysis or visualization. Data wrangling does not help the analyst to acquire data from web pages,
butratherto improve the quality and usability of the data.
ETL stands for Extract, Transform, and Load, which is a process that involves moving data from one or
more sources to a destination, such as a data warehouse or a database. ETL does not help the analyst
to acquire data from web pages, but rather to store and organize the data
Question #3 (Topic: Demo Questions)
Which of the following is an example of a at flat file?
A.
CSV file
B.
PDF file
C.
JSON file
D.
JPEG file
Correct Answer: D
Explanation not available for this question.
Question #4 (Topic: Demo Questions)
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?
A.
The data analyst is not querying the databases correctly.
B.
The databases are recording different events.
C.
The databases are recording the event in different time zones.
D.
The second database is logging incorrectly.
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 #5 (Topic: Demo Questions)
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?
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.