Big Data Applied | 275
offering IoT-enabled services, venturing
into new business lines expanding from
core capabilities and making life easier and
more comfortable for people in general
through smart gadgets, smart home appli-
ances, etc.
• Recommendation engines are a key feature
of all retail websites. The recommendations
are made based on patterns of user pur-
chases, user activities in a website and also
with the trending choices made by multi-
ple users.
• Recommendations are also made by ana-
lysing the characteristics of the products
chosen by users and identifying products
with similar characteristics.
Multiple-choice Questions (1 Mark Questions)
1. State whether the following statement is
True or False.
a. A Hadoop Engineer is a Data Scientist.
(False)
2. State whether the following statement is
True or False.
a. Data Science is a combination of
Business, Computing and Statistical
knowledge. (True)
3. Which of the following is a connected
device?
a. Wearable devices such as health moni-
toring devices.
b. Smart watches
c. Home automation systems such as
lighting / heating controls.
d. All the above
4. State whether the following statement
is True or False. An analytics platform is
important to make sense of the Big Data
generated by sensors and make predic-
tions. (True)
5. Which of the following is a valid type of
recommendation?
a. Expert filtering
b. Smart filtering
c. Reliable filtering
d. Collaborative filtering
6. Point out which of the following sites
heavily use recommendation engines.
a. Netflix
b. Amazon
c. Facebook
d. All the above
Short-answer Type Questions (5 Marks Questions)
1. Define Data Science.
2. What is the Internet of Things?
3. Explain the working of a remote
health-monitoring system based on your
knowledge of IoT.
4. What are the IoT devices you use in your
everyday life?
5. Give some examples of IoT in action
adopted by large global companies.
6. Write a short note on the impact of IoT on
consumer lifestyle.
7. What is content-based filtering?
8. How does Netflix recommend the movies a
user may watch?
M10 Big Data Simplified XXXX 01.indd 275 5/13/2019 9:56:49 PM
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