October 11, 2024

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Cybersecurity vs Data Science Career: Comparative Study

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Each day, we generate 328.77 million terabytes of data. And this number is expected to reach 463 million terabytes by 2025 (Source: ciobulletin.com).

Businesses are leveraging this data to understand their customers better. Not surprisingly, small and big businesses agree that data empowers them to make better business decisions and enables key strategic initiatives. Plus, it aids in improving the relationship with both customers and business partners (Source: The Analytics Advantage | Deloitte).

Now, with data gaining traction for business decisions, data breach incidents are also rising in alarming numbers. The latter has further propelled a staggering demand for cybersecurity experts as well as businesses need expert help to protect the data assets. Thus, looking at the contemporary job market, two fields are making a buzz- Data Science and Cybersecurity.  But, which one to choose between Cybersecurity Vs Data Science Career options?

This blog embarks on a comparative journey between the two domains, examining their respective scopes to understand Cybersecurity Vs Data Science which is better? 

What is Cybersecurity? 

Each organisation uses networks, systems, and devices for smooth operations. As these units hold sensitive data and offer easy access to an organisation’s resources, these are a prime target of hackers. Cyber security is the technology to protect networks, systems, devices, and data from unauthorised access, attacks, or damage launched by the hackers. The domain shoulders the responsibility of maintaining the confidentiality, integrity, and availability of information and resources

With the exponential growth of cybercrimes, a career in cybersecurity brings in huge opportunities. A cybersecurity professional assesses potential threats and risks, develops security policies, and quickly responds to cyber security incidents.

What is Data Science? 

Every organisation generates data that help them in running their businesses smoothly. Data science helps organisations clean, sort, analyse, and present this data in easily legible insights – that help to steer informed decisions or identify trends.  Data science is a multidisciplinary field, combining several domains like statistics, mathematics, programming, machine learning, data mining, etc.

With businesses inclining to data-driven operations, a career in data science is highly lucrative. Data scientists play a vital role in helping organisations make informed decisions, optimise processes, and gain a competitive edge in the market. Data science professionals are responsible for collecting, cleaning, analysing, visualising, and communicating data to solve real-world problems or drive strategic i decisions.

Why A Career in Cybersecurity? 

With growing instances of hacking incidents, the demand for skilled cyber security is growing exponentially. But unfortunately, there are not enough cybersecurity professionals in the market today. A cybersecurity career is highly promising (Source: Garter). In India alone, there will be 1 million cybersecurity professionals by 2025 (source: NASSCOM-DSCI). And this skill-gap brings out a great opportunity for those looking to enter the field.

Cybersecurity offers varied career paths and opportunities for growth and advancement. Cybersecurity professionals can work in different sectors such as government, banking, healthcare, e-commerce, education, etc. Not surprisingly, these professionals have great scope for higher income. An entry-level cybersecurity professional in India can earn around ₹ 8 lakhs per annum.

Apart from high salaries, studies show that cybersecurity professionals have a higher level of job satisfaction. A recent survey found that 71% of security professionals are satisfied with their jobs (Brathwaite, S., 2022).

How to enter the field of cybersecurity?

Cyber security is a multidisciplinary domain, where a candidate comes with fundamental knowledge of programming and networking.

  1. Start with the foundation: Build your foundation in the fundamentals of cybersecurity. The foundational courses focus on various kinds of cyber attacks, different hacking methods- and also various defense methodologies.
  2. Advanced-level courses: Once done with the fundamentals, the candidate can switch to more specialisations in cybersecurity such as Certification in Cyberforensics, incident response, or pen-testing for security engineers.
  3. Certifications: Sign up for globally-recognised Cybersecurity certifications after completing intermediate or advanced courses. Cybersecurity professionals holding global certifications always earn a higher package than their non-certified counterparts. Some major global cybersecurity certifications include C|EHv12, C|PENT, CISA, and so on Leading industry-relevant certifications provide credibility to the candidate’s resume and demonstrate their hold over the subject to potential employers.
  4. Get hands-on experience: In cybersecurity, apart from theoretical knowledge, practical experience is critical for success. Candidates can work on free Dataspace Academy Labs, or AttackDefense for practical skills.

Top Job Roles in Cybersecurity

Some of the top job roles in cybersecurity are:

  1. Security Analyst: A security analyst is responsible for monitoring and analysing the security posture of an organisation’s network and systems. They also perform vulnerability assessments, penetration testing, risk analysis, and incident response.
  2. Security Engineer: A security engineer is responsible for designing, implementing, and maintaining security solutions for an organisation’s network and systems.
  3. Security Architect: A security architect is responsible for creating, developing, and overseeing the security architecture for an organisation’s network and systems. They also ensure that security policies, standards, and best practices are followed.
  4. Security Consultant: A security consultant is responsible for providing expert advice and guidance on various aspects of cybersecurity to an organisation or a client. They also conduct audits, assessments, and reviews of the security posture of an organisation or a client.
  5. Penetration Tester: A penetration tester is responsible for conducting simulated attacks on an organisation’s network and systems to identify and exploit any vulnerabilities or weaknesses. They also provide recommendations on how to improve the security defenses and prevent future attacks.

Top Industries Looking for Cybersecurity Professionals

Some of the top industries looking for cybersecurity professionals are:

  1. Banking and Finance: The banking and finance sector deals with sensitive and confidential data such as customer information, transactions, accounts, etc. Therefore, they need cybersecurity professionals to protect their data from cyberattacks such as phishing, ransomware, DDoS, etc.
  2. Healthcare: The healthcare sector deals with critical and personal data such as patient records, medical history, diagnosis, treatment, etc. They need cybersecurity professionals to protect their data from cyberattacks such as data breaches, malware infection, identity theft, etc.
  3. E-commerce: This sector deals with huge amounts of data such as customer details, orders, payments, inventory, etc. Therefore, they need cybersecurity professionals to protect their data from cyberattacks such as credit card fraud, account hijacking, data theft, etc.
  4. Education: This sector deals with valuable and intellectual data such as student information, grades, research papers, curriculum, etc. Therefore, they need cybersecurity professionals to protect their data from cyberattacks such as hacking, plagiarism, cyberbullying, etc.
  5. Government: This sector deals with sensitive and classified data such as national security, public services, citizen records, policies, etc. Thus, they need cybersecurity professionals to protect their data from cyberattacks such as espionage, sabotage, cyber warfare, etc.

Why a Career in Data Science? 

Data science is one of the most popular and rewarding fields in the IT industry today. According to a report by IBM, India will have an 11% share of global demand for data science jobs by 2025. The average salary of a data science professional in India is around ₹ 10 lakhs per annum, according to Glassdoor.

Data science also offers a variety of career paths and opportunities for growth and innovation. Data science professionals can work in different sectors such as e-commerce, healthcare, banking, education, retail, etc. They can also choose from various job roles such as data analyst, data engineer,

data scientist, machine learning engineer, business analyst, etc.

How To Enter the Field of Data Science?

Since data science is a multidisciplinary field, anyone trying to build a career in this domain requires skill and experience in either software engineering or programming. The most popular programming languages for data scientists are SQL, Python, Java, R, Scala, and so on.

1. Education and Qualifications

Pursuing a bachelor’s degree in fields such as mathematics, statistics, computer science, or a related discipline provides a strong starting point. Additionally, consider obtaining a master’s degree or a PhD in data science or a specialised area within the field to enhance your knowledge and credentials.

2. Develop Strong Analytical and Technical Skills

Data science heavily relies on analytical thinking and proficiency in various technical tools and programming languages. Strengthen your skills in statistics, mathematics, and data analysis techniques. Familiarise yourself with programming languages like Python, R, or SQL, which are commonly used in data science. Enrolling in online data science certification courses or attending workshops can be beneficial for honing these skills.

3. Gain Practical Experience

A portfolio of practical projects is vital to showcase your skills and expertise to potential employers. Participate in Kaggle competitions, contribute to open-source projects, or take on data science internships to gain hands-on experience. Practical projects not only allow you to apply your knowledge but also demonstrate your ability to solve real-world problems using data science techniques.

4. Continuous Learning to Stay Updated

Stay updated with the latest trends by following reputable data science blogs, attending conferences, and engaging in online communities. Participate in online courses or certifications to acquire new skills and stay ahead in this dynamic field.

5. Networking and Professional Engagement

Networking plays a crucial role in the data science community. Join data science groups on social media platforms, attend local meetups, and connect with professionals already established in the field. Engaging with the community opens up opportunities for mentorship, collaborations, and valuable insights into the industry.

Top Job Roles in Data Science

Here are some of the top data science career options:

  • Data Scientist: A data scientist is responsible for applying advanced methods and techniques such as machine learning and deep learning to extract insights and value from large amounts of complex data. They also create predictive models and algorithms to solve real-world problems or make informed decisions.
  • Data Analyst: A data analyst is responsible for collecting, cleaning, exploring, and analysing data using various tools and techniques. They also create reports and dashboards to communicate their findings and insights to stakeholders or clients.
  • Machine Learning Engineer: ML Engineers help in researching, building, and designing the artificial intelligence responsible for machine learning. These engineers also work to maintain and enhance existing AI systems.
  • Data Engineer: A data engineer is responsible for building and maintaining the data infrastructure and pipelines for an organisation or a project. They also ensure that the data is reliable and accessible for analysis or modelling purposes.

Top Industries Looking for Data Science Professionals

Here are some of the key industries where data science professionals are in high demand.

  1. E-commerce: The retail industry counts ondata scientists to enhance customer experience and satisfaction by providing personalised recommendations, based on customer behaviour or preferences. They also use data science to optimise their operations or processes such as inventory management or logistics by using predictive analytics or optimisation techniques.
  2. Healthcare: In the healthcare industry, data science helps in patient diagnosis and treatment, drug discovery, and healthcare analytics. Usage of data science in this field helps analyse vast amounts of medical data to improve patient outcomes, optimise healthcare operations, and support research.
  3. Finance and Banking: The finance and banking sector extensively uses science for risk analysis, fraud detection, customer segmentation, algorithmic trading, and personalised financial services. It is a highly sought-after domain that helps extract insights from financial data and develop predictive models.
  4. Telecommunications: Data science helps understand customer usage patterns, improves network performance, and optimises pricing plans. Data scientists play a crucial role in optimising network infrastructure and providing personalised services.

Apart from these industries, data science is used in transport and logistics, manufacturing, marketing and advertising, etc. With the rise of data-driven decision-making and the value of extracting insights from data in various domains, more industries will enter this list.

When talking about data science or cyber security which is better, you have to remember that these two domains are among the in-demand and lucrative fields in the IT industry. Both of them deal with complex and challenging problems that require analytical and technical skills.

Cybersecurity vs Data Science

Here is a brief difference between these two domains.

Area of Difference  Cybersecurity Data Science
Focus Protecting computer systems, networks, and data Extracting insights and knowledge from large datasets
Goals Ensure confidentiality, integrity, and availability of data Uncover patterns, trends, and correlations for decision-making
Skill Sets Network security, cryptography, risk assessment Programming, statistics, machine learning, data visualisation
Approach Proactive implementation of security controls Exploratory analysis, modelling, algorithm application
Impact Preventing breaches, protecting privacy, mitigating risks Data-driven decision-making, optimisation, innovation

Wrapping Up

Understandably, data is a valuable asset for any organisation. Unfortunately, hackers know that as well. Organisations are grappling with cyberattacks. So questions such as ‘data science or cyber security which is better’ are futile. Both these domains are highly popular and can offer you immense scope for career development. DataSpace Academy is one of the premier institutions offering you hands-on training as well as placement assistance on their cyber security and data science courses.

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