Businesses today are overflowing with data. The amount of data produced every day is truly staggering. A study by Forbes a few years ago confirmed the Data Explosion. It was found in the study that nearly 2.5 quintillion bytes of data is generated every day. Because of this Data Explosion, it has become seemingly difficult to capture, process, and store big or complex datasets.

With every sector, from Financial Institutions to the Healthcare Industry, moving their Information Systems online, there has been an ever-increasing pressure to protect computer systems and networks from unauthorized intrusions and security breaches.

This article provides a detailed overview of the role of Data Analytics in Cyber Security. This article is about who Security Data Analysts are, and what are their Key Roles and Responsibilities.

Cyber Security and Data Analytics Overview

Cyber Security is usually defined as the use of techniques or skills to protect computer networks and digital assets from attack. You probably know someone who has been hacked or even just lost control of their Facebook account for a few hours, and the bigger attacks are always in the news. Pegasus Spyware, rings a bell? Data breaches in large organizations/corporations mean that millions of people can have their data stolen. Cyber Security experts are the ones who are able to fight Cyber Criminals on their own turf, stopping them from breaking into your networks and accessing important information.

Cyber Security Analysts play a vital role in assessing Cyber Threats, installing security systems, identifying and correcting the flaws in those security systems from time to time, and, in the event of a breach, implementing a recovery plan. To excel in this field, pursuing an online master’s in Cyber Security can provide advanced knowledge and skills in data protection, threat detection, and risk management.

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But how do you identify Cyber Threats or malicious activities in the first place?

Data Analytics plays a very significant role in identifying internal and external risks businesses face because of technology and the Internet. It helps detect possible fraud, unusual network traffic, and security breaches and transforms data into actionable insights for enhancing security. 

A Security Data Analyst uses Data Analytics specifically for Cyber Security and analyzes data from various sources to improve security measures. Their work focuses on monitoring and analyzing network traffic to prevent or detect malicious activities, making them a crucial element in enhancing an organization’s security posture.

6 Key Responsibilities of a Security Data Analyst

The responsibilities of a Cyber Security Data Analyst vary from place to place and depend on a variety of factors. But a majority of Security Data Analysts will have to use Data Analysis techniques to create valuable intelligence to further improve the security system. To do so, the analyst needs to be well versed in all stages of Data Analytics. Given below are the 6 Key Responsibilities of a Cyber Data Analyst:

1) Data Mining

Collecting data from the company database or extracting it from external sources to do any sort of research is one of the major roles of not just a Security Data Analyst, but any Data Analyst for that matter. Data Mining is a process of extracting and structuring large raw datasets, and recognizing the various patterns in the data through mathematical and computational algorithms. This helps to generate new information and unlock various valuable insights. Cyber Security Data Analysts need to monitor the large set of activities related to the systems and user behaviour, especially potentially suspicious behaviour, in order to keep threats away.

Data Cleaning is the next step in the overall data preparation process. It is the process of analyzing and identifying relevant data from the raw organizational datasets to make security decisions. Data Cleaning also involves standardizing the data into a single format.

2) Analyzing Data

Needless to say, this role is a must for any Data Analyst. Data Analytics is the art of exploring the facts from the data but to answer a specific question. It is the process of evaluating data using analytical and logical reasoning to examine each data component collected from security systems. For those pursuing a career in this field, preparing for certifications like the CompTIA Certification Exam can provide a solid foundation in key cybersecurity principles. A Security Data Analyst needs to analyze network traffic to detect patterns that indicate a potential attack.

A Cyber Security Data Analyst uses standard Security Analytics Tools to analyze and interpret the data.

3) Behavioral Analytics

A Security Data Analyst makes use of Behavioral Analytics to examine the patterns and behavioural trends of users and systems to identify suspicious behaviour that could indicate a potential security attack or breach.

4) Real-Time Intrusion Detection

It isn’t easy to monitor and hunt down vulnerabilities in real-time. With the help of Security Information and Event Management (SIEM) tools, it is possible for a Cyber Data Analyst to fetch data and carry out real-time analysis of security alerts generated by network devices and applications. This real-time analytics helps to detect any malicious activities happening in the system.

Cyber Data Analysts also analyze the historical and current data from security systems for studying and predicting the threat patterns. This approach can help in preventing the company from future Cyber Attacks.

5) Forensics

Cyber Security Data Analysts work to protect a company’s computer systems and networks from Cyber Attacks. But in reality, no system can be made invulnerable. So, what is the role of a Cyber Data Analyst after a Cyber Attack?

With the help of various Forensic Tools, a Cyber Data Analyst gathers Digital Evidence from a system that was compromised. They work on cases following an attack to collect Digital Evidence to retrieve information and to identify the root cause. They also intend to recover the deleted or stolen data. Forensic Tools are also used to investigate past or ongoing attacks, to determine how the attackers broke into the network systems, and hence identifying security vulnerabilities that could leave the company susceptible to a future attack.

6) Visualization and Reporting

Being able to tell a compelling story with data is crucial in getting your point across. Therefore, Data Visualization can have a make-or-break effect on your overall effort. The Data Analyst needs to know how to report results in a form that is understandable to the stakeholders. Analysts use high-quality charts and graphs to present their findings in a clear and concise way.

Apart from these niche roles, a Cyber Data Analyst may need to perform some general roles as well, like, conducting Security Assessments, performing Security Audits, formulating Security Policies and Procedures, etc.

6 Key Skills of a Security Data Analyst

Looking for a career in Cyber Security? Having defined the Roles and Responsibilities of Security Data Analysts, let’s discuss what it takes to become one. Here are some important skills that today’s Cyber Security Data Analysts should possess:

1) Knowledge of Computer Science

The role of a Cyber Data Analyst spans several disciplines. The Cyber Security Data Analyst needs to be familiar with the fundamentals of Computer Science for all stages of the Data Analysis Process, from identifying the required data to analyzing it and drawing conclusions.

2) Knowledge of Cyber Security

Of course, a Cyber Data Analyst also requires a background in Cyber Security. As discussed, Cyber Data Analysts often work to identify potential vulnerabilities in network systems. An Analyst should understand common vulnerabilities, the threats that they pose, and ways to contain these risks.

3) Experience in Working with Data

The most crucial skill that any Data Analyst should have is a penchant for data and the knowledge of how data evolves in an organization. This means he should come from a background of working with data. He/she needs to leverage these skills to analyze the data coming from various network systems.

4) Knowledge of Programming Languages

The one thing that intimidates most people about Cyber Security is the idea that you need to know how to program a computer. Understanding and writing codes can be a very valuable skill. Expertise in at least one Programming Language will be very helpful as Programming Languages like Python and R are used to analyze data and interpret the results.

5) Knowledge of Data Engineering Tools

Experience in working with Data Engineering Tools can be a tremendous advantage for any Data Analyst. Exposure to the Cloud-Based Data Warehouses like Amazon Redshift, Snowflake, and Cloud-Based ETL Tools like Hevo Data, AWS Glue, etc. are an added advantage.

6) Knowledge of Computer Forensics

Basic knowledge of Computer Forensics aids in creating evidence in the event of a breach.

Conclusion

This article provided a detailed overview of the Roles and Responsibilities of a Security Data Analyst. Data Analytics for Cyber Security can do wonders and it can really strengthen the ability of organizations to deal with attacks and data breaches.

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FAQs

1. How does a Security Data Analyst ensure compliance?

They monitor and report on adherence to regulatory frameworks like GDPR, HIPAA, or PCI DSS.

2. How does a Security Data Analyst detect threats?

They utilize security tools such as SIEM, analyze network data, and correlate patterns to be able to identify potential threats and vulnerabilities.

3. How do Security Data Analysts handle false positives?

They refine the detection algorithms and use advanced analytics in order to minimize and manage false-positive alerts.

Raj Verma
Business Analyst, Hevo Data

Raj, a data analyst with a knack for storytelling, empowers businesses with actionable insights. His experience, from Research Analyst at Hevo to Senior Executive at Disney+ Hotstar, translates complex marketing data into strategies that drive growth. Raj's Master's degree in Design Engineering fuels his problem-solving approach to data analysis.