Cybersecurity vs. Data Science

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. 

What Is Data Science?

Data science is an interdisciplinary field that uses statistics, computing, mathematics, and domain expertise to collect, prepare, analyze, and interpret data in order to generate meaningful insights. It is broader than big data analytics: big data analytics focuses mainly on extracting patterns from very large datasets, whereas data science also includes problem framing, experimentation, modeling, machine learning, interpretation, and communication.

In contemporary practice, data science is closely tied to AI, since data scientists often help build, evaluate, and monitor machine learning and AI systems in addition to analyzing data. In the hands of a qualified professional, data can support evidence-based decisions, improve efficiency, and drive innovation across industries.

Education Requirements for a Career in Data Science

Individuals pursuing a career in data science typically need at least a bachelor’s degree in a field such as data science, computer science, statistics, mathematics, engineering, or information science. For more advanced, research-oriented, or specialized roles, employers may prefer or require a master’s or doctoral degree. A graduate degree in data science is the most direct path, although related graduate study can also be useful depending on the specialization. For example, cybersecurity may be relevant when a role involves fraud detection, anomaly detection, threat intelligence, or the integrity and protection of data systems, but it is not a substitute for core preparation in statistics, programming, and modeling.

In addition to formal education, candidates may strengthen their qualifications through research experience, portfolio projects, internships, and technical specialization. Certifications can also help, especially when they complement demonstrable skills rather than replace them.

Data Science Certifications

Because data science includes multiple career paths, certifications are best selected according to role rather than treated as one general requirement.

For entry-level or general data science preparation, the IBM Data Science Professional Certificate provides a practical foundation in Python, SQL, Jupyter notebooks, data analysis, and machine learning, while DASCA’s Senior Data Scientist (SDS) is more appropriate for experienced professionals seeking a broader, vendor-neutral credential in advanced data science and leadership.

For analyst and business intelligence roles, relevant options include the Microsoft Certified: Power BI Data Analyst Associate, the Databricks Certified Data Analyst Associate, and Tableau certifications. For data engineering, strong choices include the Google Cloud Professional Data Engineer and the Databricks Certified Data Engineer Associate.

For machine learning and AI-oriented roles, the AWS Certified Machine Learning Engineer – Associate, the SAS Certified Professional: Artificial Intelligence and Machine Learning, and NVIDIA’s Deep Learning Institute certifications are especially relevant. Candidates working in Microsoft’s AI ecosystem should also note that the Azure Data Scientist Associate is being retired in 2026 in favor of a newer MLOps Engineer path.

Overall, certifications can strengthen a professional profile, but they are most valuable when aligned with a specific career direction and supported by real project work and technical depth.

Career Paths in Data Science

Data science supports several related career paths, but these roles are not identical.

• Data Analyst: focuses on cleaning, exploring, and interpreting data to support reporting and decision-making.
• Data Scientist: focuses more broadly on statistical analysis, experimentation, predictive modeling, and machine learning.
• Data Engineer: builds and maintains the systems, pipelines, and storage infrastructure that make data usable at scale.
• Machine Learning Engineer: develops, deploys, and maintains machine learning systems in production environments.
• Business Intelligence or Analytics Professional: emphasizes dashboards, performance metrics, and operational insight.

If you want a single labor-market reference point, the U.S. Bureau of Labor Statistics reports that data scientists had a median annual wage of $112,590 in May 2024, and the occupation is projected to grow 34% from 2024 to 2034, which is much faster than average.

What’s the Difference Between Cybersecurity vs Data Science?

Cybersecurity and data science overlap in some settings, but they are different fields. Cybersecurity is primarily concerned with protecting systems, networks, and data from unauthorized access, misuse, and attack. Data science is primarily concerned with extracting insight and value from data through analysis, modeling, and interpretation.

The two may intersect in areas such as fraud detection, anomaly detection, risk scoring, and threat intelligence, but their main goals are different: cybersecurity focuses on defense and protection, while data science focuses on analysis, prediction, and decision support.

Cybersecurity vs. Data Science at a Glance

	Cybersecurity	Data Science
Main Goal	Protect data, networks, systems from threats & attacks	Analyze data to uncover insights, trends, and support decision-making
Typical Work	Detect vulnerabilities, defend systems, respond to cyber threats	Collect, clean, model and interpret data; build predictive/statistical models
Core Skills	Security tools & protocols, network defense, risk detection, system monitoring	Programming, statistics, data cleaning, modeling, analytics, visualization
Best For	People who like security, protection tasks, detective-style problem solving	People who enjoy data, patterns, analytics, research, extracting meaning
Common Roles	Security analyst, ethical hacker/penetration tester, security engineer	Data analyst, data engineer, machine learning engineer, analytics roles
Work Context	Security teams, IT departments, companies needing protection, government, defense	Tech companies, business operations, research, marketing, product teams

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. 

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. 

Future Trends and Opportunities

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. 

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.