Deciding between cyber security vs. data analytics? Due to the nature of the online world, the IT industry is always evolving and adapting. Each year comes with its own set of new advancements, requirements, abilities, and threats.
However, because the world is moving at such a pace, there is a severe shortage in filling the important jobs. That leaves us with cyber security and data analytics, two fields with one thing in common. They are among the most desired by employers right now.
Because they are critical to modern workplaces, getting experience and qualifications in either of these sectors is a gold mine. Having said that, despite the two job roles having one thing in common, they are actually different career paths. Some people often have a tricky time choosing the best one for them.
Fortunately for you, we have created a guide on cyber security vs. data analytics, and the key differences between them.
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Cyber security vs. data analytics…Read below to know more!
What is Cyber Security?
Cyber security is the practice of protecting computers, servers, mobile devices, electronic systems, networks, and data from digital attacks, theft, and damage. It involves implementing technologies, processes, and policies to secure information and prevent unauthorized access, use, disclosure, disruption, modification, or destruction.
Cyber security threats can come from various sources, including hackers, cyber criminals, state-sponsored actors, and malware. These threats can take many forms, such as phishing scams, ransomware attacks, data breaches, and network intrusions. Cyber security professionals use a variety of techniques and tools, such as firewalls, encryption, multi-factor authentication, and threat intelligence, to detect and defend against these threats.
The importance of cyber security has increased dramatically in recent years as more and more sensitive information is stored and transmitted electronically. Businesses, governments, and individuals must take proactive measures to protect themselves from cyber security threats, as the consequences of a successful attack can be devastating, including financial loss, reputational damage, and loss of sensitive information.
What is Data Analytics?
Data analytics is the process of analyzing and interpreting large and complex data sets to extract meaningful insights and drive informed decision-making. It involves using mathematical and statistical methods, as well as various tools and technologies, to uncover patterns, relationships, and trends in data.
Data analytics can be applied in a wide range of industries and applications, including business, finance, healthcare, marketing, and sports. The goal of data analytics is to turn raw data into actionable insights that can inform business strategy, improve operations, and drive innovation.
Cyber Security vs Data Analytics – The Differences
This is a question a lot of people ask, especially just before choosing their route into the world of IT. What is the difference between cyber security and data analytics? Don’t they both basically deal with data?
Of course, there are similarities because both job titles work within the same umbrella of IT, however, they are very different roles. Cyber security is all about keeping confidential data safe and out of the wrong hands, while data analytics is about putting that data in the right hands in order to make the best possible decisions for the company.
Let’s take a look at some comparisons across the key parts of the jobs, including the responsibilities, education, salary, prospects, and more.
Being a cyber security professional is all about protecting the information your company wants to keep out of the hands of any attackers. The important thing to remember is that attackers do not always come in the form you may think. Companies often want to keep sensitive data away from certain employees as much as they do strangers. Therefore, cyber security professionals use an array of techniques to keep information and networks secure, while preventing and dealing with any attacks, breaches, malware, etc.
The day-to-day life of a data analyst is about collecting data from a wide array of sources and piecing it together to create meaningful information. At first, data always seems like a collection of random numbers on a page. However, it is the job of a data scientist or analyst to take unstructured and structured data and turn it into insights that help the company to make important decisions for the future. For example, a company may want their data analyst to look at product sales and create a detailed profile of their consumers, based on age, gender, location, political beliefs, interests, etc.
The world of IT is often very technical and advanced, so it requires a certain level of education and understanding. It makes sense that if a company is hiring you to protect their sensitive information or shape their future decisions, they will want to know you are qualified to do so.
While a formal education is never required, it does make it easier! Some data analytics applicants may be able to earn a starting position after completing a bachelor’s degree, however, a master’s degree will be needed to make meaningful progress in your career. If you want to work your way up the ladder and take the next steps, then a master’s should be on your to-do list. Data analytics revolves around complex stats and maths, so knowing your way around the concepts and the practical application of those concepts is a must.
In contrast, a master’s degree is not so much of a necessity in the world of cyber security. A bachelor’s degree in some kind of IT or security field will likely be enough. However, you will obviously need all the skills and creativity required to actually impress in your role as a cyber security professional. It is one of those jobs that often requires certain traits that cannot be taught.
As we explained before, both of these roles come with high demand and lower supply, which is always a recipe for a good salary. The salary range for cyber security or data analysts can vary widely based on several factors such as location, industry, company size, and level of experience.
In general, the median salary for data analysts in the United States is around $60,000 to $80,000 per year. However, data analysts with advanced skills and several years of experience can earn salaries well over $100,000 per year. It’s worth noting that the salary range for data analysts can also vary greatly based on the industry they work in, with some industries such as technology, finance, and healthcare offering higher salaries than others.
According to Glassdoor, the median salary for cyber security analysts in the United States is approximately $80,000 per year, with salaries ranging from around $60,000 to $110,000 or more. However, highly skilled and experienced cyber security analysts can earn salaries in excess of $140,000 or more, particularly in industries such as technology, finance, and healthcare that place a high value on cyber security expertise. It’s worth noting that salaries for cyber security professionals tend to be higher compared to other IT roles due to the high demand for their skills.
To put it simply, the internet is going nowhere. And while the internet is around, there will always be a need for data analysts and cyber security professionals. So, the basic prospects in both job roles are pretty wide and secure for the foreseeable future.
It’s estimated by the US Bureau of Labor Statistics the field of analytics will grow by 23% between 2021 and 2031.
The global cyber security market is expected to reach $376 billion by 2029, driven by increasing cyber threats and data breaches. This high demand for cyber security experts means that there are many job opportunities available in a variety of industries, including government, finance, healthcare, and technology.
Data Analytics Skills and Tools
Strong mathematical and statistical skills: Data analytics requires a strong understanding of mathematical and statistical concepts, such as probability, regression analysis, hypothesis testing, and statistical inference. This includes the ability to apply these concepts to real-world data sets to identify trends, patterns, and relationships.
Proficiency in data analysis tools and programming languages: Data analytics professionals should have experience with data analysis tools, such as R, Python, SQL, and SAS, as well as be able to program in at least one of these languages. This allows them to access, manipulate, and analyze large and complex data sets, as well as create models to solve specific business problems.
Data visualization skills: Data visualization is a key component of data analytics, as it allows data analysts to present insights in a clear and easily understandable format. A good understanding of data visualization techniques, tools, and best practices is essential to effectively communicate insights to stakeholders.
Data interpretation and critical thinking skills: Data analytics professionals must be able to interpret data and use critical thinking skills to identify trends, patterns, and insights that can inform business decisions. This requires the ability to analyze large and complex data sets, draw conclusions, and make recommendations based on the data.
Experience with big data technologies: With the growth of big data, experience with big data technologies, such as Hadoop and Spark, is becoming increasingly important in the field of data analytics. These technologies allow data analysts to process and analyze large and complex data sets in real-time, providing valuable insights for businesses.
Soft Skills for Data Analytics
Attention to detail: Data analytics requires a high level of accuracy and attention to detail, as even small errors in data can lead to incorrect conclusions and decisions. This requires a strong focus on data quality and the ability to validate data sources and assumptions.
Adaptability and a willingness to learn:It’s essential for data analytics professionals to continuously stay up to date with emerging technologies and best practices. This requires a strong commitment to learning and professional development.
Strong communication and collaboration skills: Data analytics professionals must communicate complex data insights and findings to non-technical stakeholders in a clear and concise manner. Collaboration skills are also crucial to work effectively with cross-functional teams, such as data scientists, business analysts, and subject matter experts, to ensure that data insights align with business goals.
Business acumen: Data analytics is not just about technical skills, but also about business knowledge. A good understanding of business operations, processes, and decision-making is important in data analytics, as the goal is to provide insights that can drive business decisions.
Cyber Security Skills and Tools
Knowledge of network security and architecture: A deep understanding of how networks are designed and secured is crucial in the field of cyber security. This includes knowledge of different networking technologies, topologies, protocols, and the potential security threats associated with them.
Familiarity with different operating systems and platforms: Security professionals need to be familiar with different operating systems and platforms, including Windows, Linux, iOS, etc., to be able to identify and address security issues in these environments.
Expertise in security protocols and encryption technologies: Familiarity with various security protocols, such as SSL/TLS, IPSec, and SSH, is crucial in ensuring secure communication over networks. Knowledge of encryption technologies, such as AES, RSA, and Elliptic Curve Cryptography, is also important to secure data in storage and transit.
Ability to perform vulnerability assessments and penetration testing: Cyber security professionals should be able to perform vulnerability assessments to identify potential security weaknesses in systems and networks. They should also be able to carry out penetration testing to simulate real-world attacks and evaluate the effectiveness of existing security controls.
Understanding of firewalls, intrusion detection and prevention systems, and security information and event management (SIEM): Firewalls, intrusion detection and prevention systems, and SIEM solutions play an important role in protecting networks from cyber threats. Understanding how these technologies work and how to use them effectively is crucial for cyber security professionals.
Familiarity with security regulations, laws, and compliance standards: Cyber security professionals should have a good understanding of various security regulations, laws, and compliance standards. These include regulations and standards such as: GDPR, HIPAA, PCI DSS, NIST, etc.
Soft Skills for Cyber Security
Critical thinking and problem-solving skills: In the field of cyber security, it is essential to have strong critical thinking and problem-solving skills to identify and respond to security incidents effectively. This requires the ability to analyze complex security issues and make decisions quickly under pressure.
Strong communication and collaboration skills: Security professionals often work in teams, and it’s essential to have strong communication and collaboration skills to work effectively with others. This includes the ability to explain security concepts to non-technical stakeholders and to collaborate with other teams, such as incident response and legal, to address security incidents.
Continuous learning and staying up to date with emerging security threats and technologies: The cyber security landscape is constantly evolving, and it is crucial for cyber security professionals to continuously learn and stay up to date with emerging security threats and technologies. This requires a strong commitment to learning and professional development.
Finding Jobs in Cyber Security vs. Data Analytics
While there are differences between the jobs themselves, searching for a job is rather similar. There are a number of things you can do to give yourself the best chance of landing an interview:
Attending networking events is a great way to meet employers looking to hire cyber security professionals or data analysts. It’s also always good to meet like-minded people, get your name out there, and talk to recruiters. Most of these events are free, so take a look at websites like Eventbrite or Meetup. Once you go to a few of these events and meet people, you will likely be invited to more. It’s also a good way to get interviews or introductions/meetings.
Ensure your LinkedIn profile is up-to-date and designed to really sell your skills and abilities. It’s a great tool for online networking and serves as your outward-facing profile to the world of employers.
Conferences are great for three things – learning new knowledge, meeting people, and having fun! Most include an opportunity to hear from speakers at the top of their field, as well as plenty of chances to network with like-minded people and potential employers. Simply by being there, it also gives the impression that you are keen to learn.
If you’re interested in attending conferences related to cyber security or data analytics, here are a few well-known ones in each field:
Cyber Security Conferences:
RSA Conference: One of the largest and most prestigious cyber security conferences, held annually in the United States.
Black Hat: A leading information security event, providing a platform for researchers to present their findings and share ideas.
DEFCON: The world’s largest underground hacking conference, held annually in Las Vegas.
BSides: A community-driven series of cyber security conferences, held in cities around the world.
SANS Institute: A cyber security training and research organization that hosts various conferences and events throughout the year.
Data Analytics Conferences:
Data Science Salon: A conference focused on AI, data science, and machine learning.
KDD Conference: A conference on knowledge discovery and data mining, held annually.
Data & Analytics Summit: A conference focused on data science, AI, and machine learning.
Spark + AI Summit: A conference focused on Apache Spark and AI, organized by Databricks.
These are just a few examples. It’s a good idea to research and find the conferences that are relevant to your interests and career goals.
Cyber Security vs. Data Analytics Research
In both fields, it’s important to stay up-to-date with the latest trends, stories, and news. Read the latest articles and blogs, listen to podcasts, subscribe to newsletters, etc. It’s important to keep learning without overwhelming yourself.
Here are a few well-known news sites and podcasts for both cyber security and data analytics:
Cyber Security News Sites and Podcasts:
Dark Reading: A website dedicated to cyber security news, analysis, and research.
Threatpost: A website focused on the latest news and analysis on cyber security threats and trends.
SecurityWeek: A website dedicated to providing in-depth coverage of information security and cyber threats.
The CyberWire: A daily podcast covering the latest news, analysis, and research in the world of cyber security.
Security Ledger: A podcast that covers the intersection of technology, security, and policy.
Risky Business: A weekly podcast that covers the latest developments in cyber security and information security.
Data Analytics News Sites and Podcasts:
KDNuggets: A website focused on data science, machine learning, and AI.
Data Science Central: A website that provides news, resources, and tutorials for data science and machine learning.
Data Skeptic: A podcast that explores the field of data science and machine learning through conversations with experts.
Linear Digressions:Explore machine learning and data science through conversations with experts and real-world examples.
These are just a few examples, and there are many more news sites and podcasts in both fields. It’s a good idea to do some research and find the ones that are relevant to your interests and career goals.
What Jobs Can I Apply for in Cyber Security and Data Analytics?
There are a number of roles within cyber security and data analytics for you to research. It’s important to find a job that fits your personal requirements and is a good fit for you.
Cyber Security Roles:
Data Analytics Roles:
Cyber Security vs. Data Analytics…Which Should I Choose?
When trying to determine a career in cyber security vs. data analytics, it is important to ask yourself a few questions. So, before judging which career path best suits these talents and passions, ask yourself:
Cyber security or data analytics are two fields that are in high demand and offer exciting opportunities.
Let’s start with cyber security. If you enjoy keeping computer systems and data secure, then cyber security might be the right choice for you. There will always be a demand for skilled cyber security professionals to keep organizations and individuals safe.
If you’re interested in working with big data used to make decisions, then data analytics might be a better fit. You’ll get to uncover patterns and insights and use your findings to support decision-making and drive business growth.
In the end, both fields require technical skills, a love of learning, and a passion for making a difference. So why not explore both and see which one resonates with you more? I’m sure you’ll make the right choice!