, Principles of Data Science
Chapter 1
What Are Data and Data Science?
Chapter Review
[1.1, LO 1.1.1, 1.1.2]
1. Select the incorrect step and goal pair of the data science cycle.
a. Data collection: collect the data so that you have something for analysis.
b. Data preparation: have the collected data stored in a server as is so that you can start
the analysis.
c. Data analysis: analyze the prepared data to retrieve some meaningful insights.
d. Data reporting: present the data in an effective way so that you can highlight the
insights found from the analysis.
Solution: b. Data preparation: have the collected data stored in a server as is so that you can
start the analysis.
Rarely is collected data already in good shape for analysis. Most of the time, collected data
needs to be processed to be suitable for the analysis of interest. An example of preparation can
be dealing with missing data—removing them or filling them.
[1.1, LO 1.1.3]
2. Which of the following best describes the evolution of data management in the data science
process?
a. Initially, data was stored locally on individual computers, but with the advent of cloud-
based systems, data is now stored on designated servers outside of local storage.
b. Data management has remained static over time, with most data scientists continuing to
store and process data locally on individual computers.
c. The need for data management arose as a result of structured data becoming
unmanageable, leading to the development of cloud-based systems for data storage.
d. Data management systems have primarily focused on analysis rather than processing,
resulting in the development of modern data warehousing solutions.
Solution: a. Initially, data was stored locally on individual computers, but with the advent of
cloud-based systems, data is now stored on designated servers outside of local storage.
11/11/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 2
Chapter 1
What Are Data and Data Science?
Chapter Review
[1.1, LO 1.1.1, 1.1.2]
1. Select the incorrect step and goal pair of the data science cycle.
a. Data collection: collect the data so that you have something for analysis.
b. Data preparation: have the collected data stored in a server as is so that you can start
the analysis.
c. Data analysis: analyze the prepared data to retrieve some meaningful insights.
d. Data reporting: present the data in an effective way so that you can highlight the
insights found from the analysis.
Solution: b. Data preparation: have the collected data stored in a server as is so that you can
start the analysis.
Rarely is collected data already in good shape for analysis. Most of the time, collected data
needs to be processed to be suitable for the analysis of interest. An example of preparation can
be dealing with missing data—removing them or filling them.
[1.1, LO 1.1.3]
2. Which of the following best describes the evolution of data management in the data science
process?
a. Initially, data was stored locally on individual computers, but with the advent of cloud-
based systems, data is now stored on designated servers outside of local storage.
b. Data management has remained static over time, with most data scientists continuing to
store and process data locally on individual computers.
c. The need for data management arose as a result of structured data becoming
unmanageable, leading to the development of cloud-based systems for data storage.
d. Data management systems have primarily focused on analysis rather than processing,
resulting in the development of modern data warehousing solutions.
Solution: a. Initially, data was stored locally on individual computers, but with the advent of
cloud-based systems, data is now stored on designated servers outside of local storage.
11/11/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 2
