Cybersecurity vs Data Science A Roadmap.pptx

Cybersecurity vs. Data Science: A Roadmap
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Table of Contents
What is Cybersecurity?
Career Scope in Cybersecurity
What is Data Science?
Career Scope in Data Science
Cybersecurity vs. Data Science
Organizations seek ways to safeguard large amounts of data and use it
effectively as technology evolves, especially in the workplace. Data
science and cybersecurity experts are in high demand due to the rising
collection of data in various sectors and the rise in cybersecurity risks.
Many people upgrade their skills and focus on one of these two fields
to meet this demand. But how do you decide which road to take?
Before deciding on a career route, you should understand the
difference between cyber security and data science.

What is Cybersecurity?
The word “cyber” means a world of computers or computer networks,
and Cyber security is the practice of safeguarding electronic data
systems against malicious or unauthorized activity. Cybercriminals are
already too clever and may simply exploit security flaws to enter data
systems. As a result, strong information security measures must be
implemented to keep data safe from unauthorized access.
Cybersecurity experts have an active mind and a strong willingness to
learn and develop innovative solutions. With the advancement of
technology, the industry demands ongoing skill upgrades to keep up
with new technology transformations.

Career Scope in Cybersecurity
Many enterprises recruit cybersecurity professionals or consultants to
protect their data and systems from security attacks. Cybersecurity
experts can assist firms in safeguarding confidential information that is
damaged in a security breach. Every organization hires cybersecurity
professionals, including banks, health, credit-card companies, e-
commerce businesses, and technological organizations. Some of the
jobs which cybersecurity professionals acquire:
 Cybersecurity Analyst
 Incident Responder
 Computer Forensics Analyst
 Cybersecurity Engineer
 Malware Analyst

What is Data Science?
Data science is concerned with the extraction and analysis of data to
make insight into it, and it’s critical for firms to identify data-driven
solutions. Data science is a set of instructions, tools, and machine
learning methods that work together to find new trends in raw data.
Planning, evaluating, explaining, deploying, and monitoring a model
are the five phases involved in data science. A Data Scientist must
have the right tools to access the relevant data, and accuracy is what
matters most in deploying any models first. Evaluating the model
allows the data scientist to improve it or replace it with a better one.

Career Scope in Data Science
The field of data science is growing in popularity and becoming more
enticing to students, and working professionals as the demand for Data
Scientists grows. Thanks to big data’s position as a different perspective
engine, Data Scientists are in high demand at the organizational level
across all vertical industries. Whether it’s to increase customer retention,
optimize product development, or mine data for new business prospects,
companies are continually relying on Data Scientist skills to stay ahead of
the competition. The following are some examples of data science jobs:
 Data Scientist
 Statistician
 Data Engineer
 Product Manager
 Lead Data Scientist

Cybersecurity vs. Data Science
Cyber security entails putting in place safeguards to prevent hackers and other
unauthorized individuals from accessing digital data systems.
On the other hand, data science takes a multidisciplinary approach because it does
not focus solely on one position. Data Scientists integrate data collection,
extraction, analysis, and manipulation to provide useful information.
While there may be a little similarity between these two professions, there are also
significant differences. To help you grasp the difference, here’s a comparison
between cybersecurity and data science:
1.Objectives: In business, the goal of cybersecurity is to secure a company’s data
and networks from unwanted access, such as cybercriminals. In contrast, data
science aims to process vast amounts of data into understandable data sets to
interpret the facts.
2. Responsibilities: Cybersecurity specialists monitor a company’s networks and
data, develop measures to safeguard such information and evaluate those methods
to verify they work properly. On the other hand, Data Scientists create theories
about data and construct algorithms to explore data more effectively. They develop
statistical models to collect and analyze massive volumes of data, then assess the
model to see where it can be improved.

3. Education: Many security experts have earned a degree in information
technology, computer science, or information systems to begin their
professions. This is their first step, following which they can pursue a
master’s or post-graduate degree in cyber security. A bachelor’s degree
in computer science, data science, or a related field, such as
mathematics, is often required for Data Scientists. After completing their
undergraduate degrees, many Data Scientists choose to pursue a
master’s degree in data science or a related field, such as data mining or
machine learning. Many data science positions demand a master’s
degree as a minimum prerequisite, and it can also assist these
individuals in developing their careers.

4. Salary: Both cybersecurity and data science jobs have the potential to pay
well, but data scientists are often known to make more money than
cybersecurity professionals. A Data Scientist’s average annual pay is
$119,378; a cybersecurity professional’s average annual salary is $94,360.
However, the salary for both occupations varies depending on the degree,
experience, company, and geographical region.
5. Job Outlook: Because businesses continue to adopt new technology to
better their operations and remain competitive, the job outlook for
cybersecurity and data science specialists is bright. According to the U.S.
Bureau of Labor Statistics (BLS), the job outlook for information security
experts, which includes cybersecurity, might increase by 33% between 2020
and 2030. On the other hand, data science is expected to grow by 22%
between 2020 and 2030.

Final Thoughts
If you want to pursue any of these courses but aren’t sure what to
do, think about your interests, technical skills, the amount of time
and dedication you’re prepared to put in, and your long-term and
short-term job ambitions. Remember that both these professions are
in high demand, and no matter which path you choose, you will
succeed.
Data science and cybersecurity are both critical parts of the twenty-
first century. As a result, you must be skilled in each of these fields.
To study more and gain a better understanding, go
to InfosecTrain’s Cybersecurity and Data Science courses.

About InfosecTrain
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