Both cyber security and data science are highly competitive and demanding professions. So, it is important for aspirants to have in-depth knowledge of these domains. Possessing the skill to communicate using figures and data is essential for both Cyber Security and Data Science. The domain of cyber security has niche career opportunities as compared to data science, which was called the sexiest job of the 21st century by a Harvard Business Review article in 2012.
In this blog, we will cover the following:
What is Cyber Security?
Cyber Security is a domain and body of knowledge consisting of technologies, practices, and processes to secure networks, systems, devices, and data from cyberthreats, cyberattacks and unauthorized access. Sometimes, cyber security is also referred to as Information Technology Security; the professionals specializing in this domain are known as cyber security experts. With the increasing volume and sophistication of cyberattacks and cyberthreats, the domain of cyber security has witnessed a threefold increase in the past few years and is expected to continue doing so.
Organizations are now focusing on onboarding the right professionals with the required skill set in cyber security. These days, almost every organization relies on the cloud for data storage. This data, which is present online, is under a cyberthreat every second. Hence, the need for a strong cyber security network is increasing with every passing day.
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What is Data Science?
Data science is the study of large and complex data sets to build analytical models for identifying insights and unlocking value-driven business decisions. The scope of data science includes machine learning, artificial intelligence, statistics, modeling, databases, and programming. The professionals specializing in the domain are known as data scientists. The process of data science typically involves obtaining raw data, converting it into analysis-ready format, and, finally, feeding it into algorithms and models to draw actionable insights.
Difference between Cyber Security and Data Science
|Basis||Cyber Security||Data Science|
|Expertise||Cyber security professionals develop strong security systems and protect organizational data, networks, systems, etc.||Data science professionals extract valuable information from raw data to build models and draw actionable insights|
|Role||The role of cyber security professionals involves protecting data and networks, monitoring security infrastructure, auditing policies, etc.||The role of data science professionals includes data analysis, building models, prescriptive analytics, machine learning, etc.|
|Education Level||A degree in either computer engineering, information security, or computer science along with relevant certifications, such as CISA, CISSP, CEH, etc., is sufficient enough to get a job in this domain.||Unlike cyber security, getting into data science requires a slightly higher education level. A data science aspirant needs to have a bachelor’s as well as a master’s in data science to have a successful career in the domain|
|Skills||The skills required for excelling in cyber security includes creative problem-solving, intrusion detection, incident response, and a strong desire to learn and upskill||Data science professionals are required to be skilled in tools such as Python and SQL; they should also have an understanding of AI and ML techniques along with an interest in mathematics and statistics|
|Job Roles||Job roles in cyber security include network engineer, cyber security analyst, systems engineer, cryptographer, etc.||Job roles in data science include data scientist, data analyst, machine learning engineer, data architect, data engineer, etc.|
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Cyber Security Career vs Data Science Career
There is a growing number of opportunities in the domains of data science and cyber security. However, it majorly depends on the preferences of individuals. This decision is based on the domain that they wish to enter and the skills possessed by them. Knowledge and interest level also play an important factor in choosing either of the domains. Even though cyber security experts are involved in niche markets, such as government, military, corporate, etc., yet they are now venturing into new opportunities in several organizations globally. On the other hand, data science professionals are in huge demand and are even paid slightly higher as compared to cyber security professionals. Now, let us have a look at some statistics below:
- As per Glassdoor, the average annual pay of a data scientist in India is around INR1,000,000 and that of an experienced data science professional is around INR2,000,000.
- As per Glassdoor, the average annual salary of a cyber security engineer in India is INR600,000 and that of an experienced cyber security professional is INR1,600,000.
- As per Glassdoor, the average annual salary of a data scientist in the USA is approx. US$100,000.
Prepare for your next job interview from our blog on Cyber Security interview questions and answers.
Importance of Cyber Security
Cyber security finds its importance and application across various sectors in the economy, such as government agencies, military, corporate, finance, medicine, etc. The entire network of data sharing (intra as well as inter) requires a strong cyber security system at place. This has also been one of the driving reasons behind the training and development of employees by organizations. We will explore some of the benefits of cyber security below:
- Data security: As a lot of organizational data is available and stored online, it is exposed to numerous threats. Implementation of the best cyber security practices ensures the protection of all kinds of sensitive or confidential organizational data.
- Mitigation of cyberattack loss: It is estimated that by 2025, cyberattacks and cybercrimes will cost the world around $10.5 trillion annually. This would, in turn, lead to customer distrust and loss of business reputation. Cyber security measures and strong network security is the only way to mitigate this loss. Hence, organizations around the globe are hiring security experts at higher remuneration levels.
- Support for digitization: With almost every customer’s data being available online due to digitization, cyber security has become pertinent for many organizations. Companies have leveraged digitization for offering ease of living to their customers. This has further increased the need for cyber security. Hence, cyber security training and development is conducted in organizations to support the ongoing digitization.
Check out our free YouTube tutorial below to know more about making a career in Cyber Security.
Importance of Data Science
It is known by almost everyone that data science has transformed the way businesses work today. Let us now understand the importance of the domain:
- Better decisions: Data science has equipped the leadership of organizations to make data-driven business decisions. Many organizations attract data scientists through high remuneration and additional benefits. This has helped organizations to explore data science and apply it for business benefits.
- Trend analysis: Trend Analysis is one of the key techniques that organizations use to set right and achievable goals. Data scientists use organizational data to recommend and prescribe the right course of action for significant solutions to business problems.
- Opportunity identification: Data science makes way for companies to identify profitable opportunities by analyzing historical data regarding customers, products, services, etc. The contribution of data scientists helps organizations explore new options for growth.
- Consumer behavior: Data science forms the base of organizational marketing and product strategy. Data scientists study consumer-related data to draw insights regarding consumer behavior. These insights assist the management to strategize and make decisions accordingly.
Go through our Data Science tutorial and learn the basics of Data Science.
There are many facts and figures saying a lot about the job opportunities in Data Science and Cyber Security domains. However, the final decision always lies with the individual. Although both domains are data-centric, they differ on the basis of skill sets, knowledge, and objectives. Hence, we recommend you to choose the domain based on your respective interest and skill set.