Cybersecurity vs. Data Science

Balkis N.

Rapid advancements in technology have driven a need for qualified professionals in the areas of data science and cybersecurity to help keep up with the breakneck pace of digital information exchanges. While data science involves using a variety of methods, procedures, and analyses of algorithms to glean data insights, cybersecurity is the process of safeguarding sensitive digital information – for both organizations and individuals – from data attacks. 

Yet, despite their differences, there are quite a few ways that the fields of cybersecurity and data science overlap and complement each other. While cybersecurity involves data protection, cybersecurity analysts must be skilled in analyzing large data sets in order to parse them for vulnerabilities and devise a means of protection. On the other side of the coin, data scientists may analyze large amounts of data, but must ensure that data is cleaned and secure in order to properly analyze it. 

Let’s take a more in-depth look at these two growing fields cybersecurity vs. data science, and the career paths they offer to curious, tech-minded professionals. 

What Is Cybersecurity?

Cybersecurity protects digital systems, networks, devices, and data from malicious cyberattacks. As a procedural science, according to the National Institutes of Standards and Technology (NIST), cybersecurity is made up of a five-function framework: 

  • Identify
  • Protect
  • Detect
  • Respond
  • Recover

Today, so much of our lives are lived online or leave a digital footprint. We shop online or via apps, entering credit card or financial information. We share personal photos and information on social media. And we even work online, with sensitive company information stored and transmitted online, ranging from employee records to proprietary company information. Factor in emerging technologies like artificial intelligence (AI) and cryptocurrency, and that cybersecurity incidents have increased by 452.51% within a five-year period, there is a growing need for qualified cybersecurity professionals to help protect digital information. A report from Cybercrime Magazine observed that there will be 3.5 million unfulfilled cybersecurity jobs worldwide in 2023 and that the cybersecurity unemployment rate is currently at zero percent. 

Education Requirements for a Career in Cybersecurity

Although it’s possible to start a career in cybersecurity with an associate’s degree, most employers require applicants to hold a bachelor’s degree in cybersecurity or a related field, such as computer science or information systems). 

More mid-level or advanced roles in cybersecurity may require applicants to hold a master’s degree, such as a Master of Science in Data Science or a Master of Science in Cybersecurity degree after earning a bachelor’s in Data Science, as the two areas are complementary. 

In addition to a bachelor’s or master’s degree, some employers also seek candidates with prior experience in the field, as well as those who hold related certifications.  

Cybersecurity certifications

Cybersecurity certifications are often a requirement for carving out a career path in the field, as they demonstrate a professional’s proficiency in a given area. Earning cybersecurity certifications can set you apart from other candidates, helping you advance your career and earning potential. There are a variety of top cybersecurity certifications that professionals can hold. These certifications require passing an exam and must be renewed periodically. 

  • Certified Information Systems Security Professional (CISSP): The CISSP is a globally-recognized certification offered by the Information Systems Security Certification Consortium (ISC)2. In order to gain this distinction, a candidate must demonstrate knowledge in eight key areas of information security, including security and risk management, security architecture and engineering, identity and access management, and more. In order to earn a CISSP, a candidate must pass the exam and have at least five years of professional experience in two or more of the eight areas of information. Those without field experience can earn this distinction via alternate paths, such as earning a bachelor’s degree in a related field.
  • Certified Ethical Hacker (CEH): The CEH certification is offered by the EC-Council, geared towards ethical hackers (sometimes referred to as penetration hackers). The exam for this certification measures a candidate’s knowledge of a variety of topics, including network security concepts, legal and ethical considerations, ethical hacking methodologies, vulnerability assessment and penetration testing, and security testing tools. 
  • CompTIA Security+: An ideal certification for entry-level professionals in cybersecurity, the CompTIA Security+ can help candidates distinguish themselves from others when pursuing intermediate-level career opportunities. The certification measures a candidate’s knowledge of troubleshooting best practices in the field, equipping them with practical security problem-solving skills. This certification is also approved by the U.S. Department of Defense.
  • Information Systems Audit and Control Association (ISACA) Certifications: Becoming a member of ISACA can help connect cybersecurity professionals to a worldwide network of peers, as well as grant access to a variety of ISACA courses. This well-respected organization offers a variety of certifications, including:
    • Certified Information Systems Auditor (CISA)
    • Certified Information Security Manager (CISM)
    • Certified in Risk and Information Systems Control (CRISC)
    • Certified Data Privacy Solutions Engineer (CDPSE)
    • Certified in the Governance of IT (CGEIT)

While these are among some of the most popular, there are several other certifications that can set cybersecurity professionals apart from their peers, including: 

  • Certified Cloud Security Professional (CCSP)
  • Offensive Security Certified Professional (OSCP)
  • GIAC Security Essentials (GSEC)

Career paths in cybersecurity

Cybersecurity presents a wealth of career opportunities that tackle different aspects of this growing field. Here are just a few of the professions to consider within the field. 

Security Analyst

A cybersecurity analyst is an organization’s first line of defense in guarding computer networks and systems from cyberattacks. They monitor networks for unusual traffic or activity, have a deep understanding around cybersecurity best practices and share that knowledge with those in their organization, and investigate data breaches that could lead to data theft and access to secure company information, or personally identifiable information (PII). 

According to the Bureau of Labor Statistics (BLS), the median annual wage for security analysts is $102,600. The need for security analysts is anticipated to increase by 35% before 2031, which is significantly faster than the average for all occupations.

Ethical Hacker/Penetration Tester

Sometimes, your best defense against hackers with bad intentions is a hacker who has the same skill set and, instead, uses their knowledge for good. In a nutshell, this describes the job of an ethical hacker (sometimes referred to as a penetration tester). These professionals assess systems for vulnerabilities, evaluate risk and develop mitigation strategies to prevent data systems from becoming compromised. According to O-Net, a division of the U.S. Department of Labor, the average median annual salary for ethical hackers is $98,740. Demand for this position is predicted to increase between 8% and 10% before 2031, which is faster than average.

Security Engineer

An information security engineer designs, implements, and maintains security systems to safeguard an organization’s data. They often work hand-in-hand with security analysts to conduct penetration testing, create a strategic defense plan, and ensure employees of an organization are compliant with these security policies. According to O-Net, information security engineers earn an average annual median salary of $98,740 and stand to see faster-than-average growth (between 8% and 10%) before 2031. 

People working on computer in dark room with server racks

What Is Data Science?

As a discipline, data science involves studying and organizing large data sets in their raw form. By ordering data, specialists in this field are able to transform – and translate that data – for organizations and individuals who lack their technological expertise. 

Data science is a growing industry that provides a variety of career paths to those who are able to “speak” the language of data and translate it for audiences. While data provides valuable insights for organizations, it can be difficult for people without the developed skill in analyzing that data to make sense of it. In the hands of a qualified data science professional, data can be used to make evidence-based decisions, as well as drive innovation and efficiency. 

Education Requirements for a Career in Data Science

Individuals hoping to pursue a career in data science will require, at minimum, a bachelor’s degree in data science or a related field, such as computer science or engineering. However, some employers may require candidates to hold a master’s degree for more senior or intermediate-level positions. A candidate with a bachelor’s in data science can consider either a Master of Science in Data Science or even a Master of Science in Cybersecurity, as the two disciplines are related, and data scientists can benefit from identifying areas where vast data stores have been compromised in terms of security or data corruption. 

In addition to a degree in data science, candidates interviewing for a data science role may also set themselves apart by obtaining certifications from recognized professional organizations in the field. 

Data science certifications

Although not required, obtaining data science certifications offered by professional organizations within the field can help distinguish professionals from others. Certifications can showcase proficiency in a given area within the data science discipline and may help you advance your career. Some of the most popular data science certifications to consider include: 

  • Senior Data Scientist (SDS) from Data Science Council of America (DASCA): Considered one of the world’s highest-ranking qualifications for data scientists, this certification places an emphasis on strategic data leadership capabilities and is vendor-neutral. In order to apply for this distinction, candidates must have at least worked for at least four years in data analytics or data engineering and application development. 
  • IBM Data Science Professional Certificate: Ideal for data science professionals early in their career, the IBM Data Science Professional Certificate demonstrates an ability to solve a variety of real-world data problems across a variety of apps, including Jupyter notebooks, SQL and Python databases, and more. 
  • SAS Certified AI and Machine Learning Professional: A certification offered by Statistical Analysis System (SAS), the Certified AI and Machine Learning Professional certification demonstrates knowledge of machine learning, natural language processing (NLP), as well as model forecasting and optimization.

Although these are some of the top certifications data science professionals may consider, there are several other certifications in this discipline that can distinguish professionals from their peers, including:

  • Professional Data Scientist (PDS) from NVIDIA Deep Learning Institute (DLI)
  • Certified Data Scientist (CDS) from Data Science Council of America (DASCA)
  • SAS Certified Data Scientist
  • SAS Certified AI and Machine Learning Professional
  • Microsoft Certified: Azure Data Scientist Associate
  • Google Cloud Professional Data Engineer

Career paths in data science

Data science stands to see exponential growth in the employment sector over the next decade and, likely, well into the future. Here are a few career avenues that data science professionals can pursue:

Data Analyst

A data analyst (sometimes referred to as an operations research analyst) collects, cleans, and analyzes data to help organizations make better, more informed decisions. In order to effectively analyze data, these professionals also “clean” it – scouring data sets for errors and inconsistencies before evaluating all data as a whole, as incorrect or corrupted data can make analyzing and modeling data less accurate.

According to the BLS, data analysts earn an annual median salary of $82,360 per year. The demand for data analysts is expected to increase by 23% by 2031, much faster than average across all operations.

Data Engineer

Data engineers (sometimes referred to as database administrators and architects) design, maintain and optimize systems that collect and store data, such as databases and data warehouses. Data engineers earn a median annual salary of $96,710. Professionals in this area of expertise can expect to see between an 8% to 10% growth in demand between 2021 and 2031. 

Machine Learning Engineer

A machine learning engineer builds and deploys software systems designed to collect, clean, and model data based on machine learning principles. They must have a deep knowledge of machine learning algorithms, as well as software engineering. According to Glassdoor, the average salary for a machine learning engineer is $133,291.

What’s the Difference Between Cybersecurity vs Data Science?

Both cybersecurity and data science both deal with complex networks and systems of information, as well as involve the analysis of large amounts of data, as well as keeping data secure. While there is some overlap between these disciplines, they each have their specific domains of expertise. In short, cybersecurity professionals are guardians of data, while data scientist professionals are analytical interpreters of data. 

At a more granular level, cybersecurity helps identify vulnerabilities and prevent attacks on data networks. Cybersecurity professionals must be comfortable looking at vast quantities of data and take a methodical approach in determining where and how threats can penetrate networks and systems. By contrast, data science involves mining vast quantities of raw data, transforming it into models and actionable insights. Those in the data scientist field need to confirm that the sizable data sets they work with are secure and free from corruption in order to arrive at accurate results. 

Skills Needed for a Career in Cybersecurity or Data Science

Undoubtedly, there is some overlap between the hard and soft skills required for a cybersecurity or data science career. Both disciplines require concrete technological skills, a knowledge of computers and data information systems, as well as mathematical, analytical, and problem-solving skills to organize large amounts of data or pinpoint any vulnerabilities. 

In terms of soft skills, both cybersecurity and data science practitioners need an innate sense of curiosity and desire to understand how complex networks of information function and understand connections between disparate systems and data sets. They also require written and verbal communication skills, with the ability to clearly log findings, create clear procedures for an organization and its employees to follow, present findings, and translate the complex world of data for others who may not have their specific skill set. 

woman in a server room reads a screen

How Do I Choose Between Cybersecurity and Data Science?

Both cybersecurity and data science are career paths poised for exponential growth in the next decade and offer ample opportunity for advancement for individuals with analytical minds and a knack for understanding complex systems. If you’re weighing your options between the two paths, consider some of your own strengths and interests that may overlap within each of these disciplines. 

Cybersecurity blends elements of computer science with criminal justice, particularly in instances where cybersecurity hones in on preventing cybercrimes. Cybersecurity may be a rewarding career path if you enjoy staying up-to-date on new technology, investigating vulnerabilities, and devising strategies to ward off cyberattacks. 

Beyond offering the limitless potential to challenge yourself intellectually, a cybersecurity career can also positively impact the lives of others. Given the prevalence of data usage and information stored online, demand will only increase for cybersecurity professionals to help keep sensitive individual, business, and even government information safe. Statistics offered by CompTIA, noted that phishing attacks increased by 48% in the first two quarters alone of 2022, costing businesses a total of $12.3 million. Similarly, the organization uncovered that “up to 40% of cyber threats are now occurring directly through the supply chain.”

On the other hand, if engineering systems and analyzing large data sets – and helping organize them in straightforward, practical ways – appeals to you, a career in data science may be more appealing. Data science, as a discipline, shares commonalities in terms of engineering as well as statistical research, albeit applied to data. 

Data science can be a rewarding career path for individuals who enjoy problem-solving and using statistical and computational techniques to transform data into insights that can be used to drive decisions offline. Data scientists have the ability to model data, using it to identify trends and predict outcomes – not just for commerce-related businesses but in areas such as the medical field and civil services that improve the quality of life for others. 

Technology is emerging at a rapid pace. While it’s hard to predict the future, it’s fairly certain that emerging technologies will soon give way to new opportunities for careers in the ever-changing digital landscape. 

Emerging technologies in cybersecurity

No emerging technology has captured people’s imagination inside and outside the tech sphere like artificial intelligence (AI). Concerning cybersecurity, AI can be used to look at massive amounts of data to detect patterns that may indicate cyber threats, as well as mitigate future security events. This pattern detection capability of AI can help cybersecurity professionals proactively identify vulnerabilities. 

Similarly, machine learning – the ability for machines to process large amounts of data, and a subdivision of AI – also presents new ways to automate threat detection and identify threats more efficiently, as well as more effectively classify malware. 

While some technologies may make it faster to identify threats, others may accelerate the need for qualified cybersecurity professionals. Quantum computing leverages quantum mechanics to process information far faster than traditional computers. Quantum computing also makes it much easier and faster to decrypt sensitive data – such as passwords. Presently, new quantum-resistant encryption standards are being developed, but organizations will need individuals trained in these methods to help roll out these measures and guard against future attacks. 

In a close parallel, the Internet of Things (IoT) – a network of devices with sensors and software that connect with other devices to exchange data – may also be vulnerable to attacks. For instance, the IoT may include devices that control industrial and infrastructure systems, such as power grids or turbines. Cybersecurity professionals will be essential to help safeguard IoT systems, especially since some may impact the safety and quality of life for people.

Emerging technologies in data science

Emerging technologies like advanced machine learning algorithms and natural language processing will also lead to a need for more professionals in data science. Machine learning engineers, for instance, can assist with creating algorithms, training models, and then optimizing them for performance. As the vast amount of data generated by humans grows, so will data warehouses and the need for qualified professionals who are able to work with ultra-large data sets to generate accurate information and model predictions. 

When combined, IoT and edge computing are also poised to deliver real-time data analysis. Edge computing views data at the precise location where that data is collected as opposed to dropping it into a cloud or data warehouse for analysis. This can lead to faster data analysis in a world that’s obsessed with garnering insights as soon as possible. 

man in dark room lit up by computer screen looking to his left

Start Your Journey at National University

Both data science and cybersecurity present a variety of career opportunities for talented minds who have an innate curiosity to understand emerging technologies and think beyond what’s right in front of them. National University can help you along your journey, no matter what stage. We are recognized by the National Security Agency (NSA) as a National Center of Academic Excellence in Cyber Defence through 2028. Additionally, NU is engaged in a five-year research partnership with the National Science Foundation (NSF) that focuses on the optimization of AI and machine learning. 

In addition to recognition from organizations at the forefront of innovation and a world-class faculty, National University offers several Bachelor’s and Master’s programs in the fields of data science and cybersecurity. 

A National University Bachelor of Science in Cybersecurity can equip you with the skills to launch a career in cybersecurity, helping protect sensitive data and equipping you with the skills needed to develop an understanding of information technology management and security processes. National University also offers a Master of Science in Cybersecurity, allowing you to take your career to new heights via a rigorous curriculum that offers a choice between two specializations: Ethical Hacking and Pen Testing or Enterprise Cybersecurity Management. 

Another option for those interested in furthering their career in data science or cybersecurity, a Master of Science in Data Science from National University can arm you with a curriculum that delves into the implementation, development, and maintenance of tools needed to effectively and efficiently use big data across four areas of specialization: Artificial Intelligence and Optimization, Database Analytics, Business Analytics, and Health Analytics. 

Frequently Asked Questions

Cybersecurity focuses on protecting digital systems, networks, devices, and data from malicious cyberattacks, while data science involves studying and organizing large data sets to provide valuable insights for organizations.

Most employers require applicants to hold a bachelor’s degree in cybersecurity or a related field, such as computer science or information systems. More advanced roles may require a master’s degree, such as a Master of Science in Data Science or a Master of Science in Cybersecurity.

Some of the top cybersecurity certifications include Certified Information Systems Security Professional (CISSP), Certified Ethical Hacker (CEH), CompTIA Security+, and various certifications offered by the Information Systems Audit and Control Association (ISACA).

Some of the top data science certifications include Senior Data Scientist (SDS) from Data Science Council of America (DASCA), IBM Data Science Professional Certificate, and SAS Certified AI and Machine Learning Professional.

In cybersecurity, some of the professions include Security Analyst, Ethical Hacker/Penetration Tester, and Security Engineer. In data science, some of the professions include Data Analyst, Data Engineer, and Machine Learning Engineer.

Learn More About Our University and Scholarships

Join our email list!

Recent Resources

Your passion. Our Programs.

Choose an Area of Study

Your passion. Our Programs.

Select a degree level

View Programs