The finance sector is not only one of the most important in the corporate world but also one that is constantly developing. Over the years, this has helped the global finance industry move with the times and give consumers the services and products they want. A good example of this in the last few decades is the way finance has integrated technology into how it operates.

This can be seen in high street banks, for example, where contactless debit cards are issued, and online banking services are standard. In the wider finance sector, you have the thriving niche of fintech, where businesses involved in the industry use the latest tech to offer cutting-edge platforms, tools, and services.

Of course, it is not just companies in the finance sector that have incorporated technology into their daily operations. Tech in the wider corporate world is just as important and underpins how efficiently any modern firm functions. From websites to email and online meetings, tech is a key aspect of contemporary business. 

Cybersecurity Is Key for Technology in Business

All modern businesses will not only collect a large amount of sensitive online data each day but will also need a safe place to store it digitally. In addition, some businesses, such as financial institutions, may need to facilitate secure online payments. When you also consider that the key systems used internally by firms need protection, the importance of cybersecurity is easy to understand. 

This gets even more pressing when you look at recent stats, which show a 38% increase in cyberattacks worldwide during 2022. This rising threat shows that all companies need to find ways to stay safe online to protect not only themselves but also their customers. As a result, experts in data analysis have become in demand around the business world for their ability to not only prevent malicious online attacks but also to play their part in dealing with them should they happen. 

What Is a Data Analyst, and How Do You Become One? 

With good rates of pay, an interesting list of responsibilities, and a bright outlook in terms of sector-wide employment, data analysis is one career many people are moving into. When you also factor in their usefulness in sifting through reams of data to help uncover actionable cybersecurity insights, you can see why it is a hot topic in global employment now. 

The first step to take if you fancy this kind of career is to get the right academic qualifications behind you. This would usually involve studying a specific higher-level program that shows you how data analytics help businesses and how it can unleash cybersecurity insights from big data in particular. The MS in Business Analytics from St. Bonaventure University online is a popular course in this area that can be completed 100% online and allows you to explore different analytic areas, including data mining within cybersecurity.

What Qualities Do You Need to Work in Data Analysis? 

As with any role you could move into for a career, data analysis calls for certain skills in order to truly excel in it. Therefore, it is key to not only know what these characteristics are but also to ensure you develop them to a high level if you plan to move into this type of job. 

The core skills and traits any data analyst should have includes: 

  • IT skills and computer programming
  • Communication
  • Problem-solving
  • Attention to detail 
  • Data visualization 
  • Understanding of statistics 
  • Teamwork
  • Critical thinking
  • Project management
  • Excellent math knowledge

While this does not show every skill or characteristic that may be called for when working in this position, it does pull together the ones that should prove most useful. If you plan to follow this career path, you should make sure you have the right combination of talents above and take the time to work on any areas you might feel weaker in. 

Data Analysts Are Key for Using Big Data to Aid Cybersecurity Efforts 

Although a business may have a dedicated IT manager and IT team, they alone may not be enough to fully guard against the daily threat of cybercrime. This is because these staff may be busy with other tasks that keep a firm’s IT systems running or may not have the skills to tease out actionable cybersecurity nuggets from big data. 

When you see the colossal amount of data even the smallest business can generate in a week or month, it is easy to see how staff with the skills and time to properly focus on it are required. This is where data analysts come in and where they can prove so handy for a company’s cybersecurity efforts especially. 

But how can data analysts unleash key insights from this vast amount of information? 

Monitoring Past Data to Enhance Corporate Cybersecurity 

This is a key technique used within data analytics and helps professionals in the industry draw relevant observations around online security from past data collected. As you can imagine, this can cause them to have to comb through reams of data in order to pick up on anything that may prove useful to know about.

One of the main things data analysts will do when monitoring past data is to look for patterns that recur and whether this might signal a cybersecurity problem. This may be the same IP address trying to access a firm’s network multiple times per day for a week at the same time. Although this may be nothing to worry about, patterns like this can be flagged to investigate further and ascertain if it is a malicious type of activity that is targeting the firm’s IT network. 

In addition, data analysts will also look at the data collected, which could flag a gap or weakness in a company’s online defenses. This could be data, for example, on any breaches that have happened recently and where they occurred on the network. By picking up on this, analysts may then be able to recommend where a business’s online defenses need upgrading or what type of attacks are most common to guard against.

Real-Time Analysis Is Also Crucial 

Alongside looking through previously collected data for patterns to aid cybersecurity, analysts will also keep an eye on real-time data to help. As you might expect, this does broadly the same thing but involves real-time information reported by their employers’ IT network. 

The main benefit of this approach is that it enables analysts to have a much better idea of what is happening right now and also be better placed to respond to any emerging threats instantly.

If they pick up on suspicious network activity and flag it before it develops into a fully-fledged cyberattack, this is much better than trying to deal with the problem after it has become an issue. By quickly analyzing data in real-time, professionals in this role can detect digital security incidents quickly, report what they have discovered, and help mitigate their overall impact. 

Focusing on Risk Management Can Help Drive Useful Insights 

Risk management and compliance are very important for all firms in the modern world. If they do not pay attention to this, online cybercrime breaches may cost them dearly in fines from regulatory bodies. Embedding data analytics into risk management processes around online security has been found to have a positive impact in this area. As a result, data analysts can use their expert skills to help the companies they work for enhance their risk management process. 

But what are the most common ways analysts will go about this and draw key insights from the large amounts of data they look over? In simple terms, analysts can help identify risks, mitigate against them, and report on them. This can then help companies ensure they are doing all they can to not only manage cyber threats but also stay within any legal frameworks they are bound by. 

Predictive Analysis in Cybersecurity for Business

It is no surprise to see that as well as taking insights from old datasets and keeping an eye on current, real-time information, analysts will also use a predictive approach in their role. This helps organizations proactively anticipate any future cyber threats or where the next wave of hacking attempts may stem from based on what current data may suggest for the future. 

By analyzing big data in this way, data analysts can pick up on patterns contained within them and use this to make predictive models of where things may head next. This allows companies to zero in on potential future attack vectors they may not be prepared for yet and stay one step ahead of emerging cybercrime attempts. 

Latest Tech Is Key for Unleashing Big Data Cybersecurity Insights 

It is no surprise to see that emerging technology plays a big part in the modern business world. The latest tech also plays a major role in how data analysts can draw out useful information from huge datasets. This is often the quickest and most efficient way to go about it – especially if the amount of data to sift through would be too much for the human eye to handle. 

A good example of how tech is used by data analysts in this way is artificial intelligence. People who work in this role are using AI to look for often complex patterns in big data that humans may miss or not be able to interpret properly. By doing this with cybersecurity in mind, AI software can be used by analysts to identify any suspicious network activity to flag.

Machine learning is also something that is being used more within data analysis for cybersecurity. This is because it allows machines to be programmed with data analysis algorithms that automatically pick up on suspicious activity and report back on any issues they spot. 

Of course, the tools and platforms used in data analysis are also essential in terms of drawing out key digital security insights from big data. Whether this is a data analytics package helping you understand where a data leak occurred or an analytics software showing you which user accounts have been compromised, this kind of tech is also key for showing you what you need to know out of all the data collected each day. 

Five Best Practices to Follow in Analyzing Big Data for Cybersecurity Insights

Although the above sets out the most common ways data analysts unearth useful information from big data, people looking at moving into this career may still wonder just how best to implement them. Luckily, the industry has adopted some procedures in this area, which make it easier. 

But what are the most important best practices to know about? 

Clearly Define Your Objectives 

The first step before reviewing big datasets with cybersecurity insights in mind is to be clear about your goals. For example, you should set out the specific issue you are looking for, such as threat detection or incident response, and make sure to focus on this. When you clearly define your objectives when analyzing data, it becomes easier to gain the insights you are looking for. 

Ensure Data Is Top Quality 

It goes without saying that data analysts are only as good as the data they are looking at. It is, therefore, key to ensure the big datasets you are reviewing contain accurate and quality information. A good tip to help is to bring in effective data governance procedures that help maintain data integrity. You can also validate and verify sources of IT and cybersecurity data to uphold standards around information quality.

Think About Using Advanced Techniques 

We have already mentioned a few advanced ways of drawing cybersecurity recommendations from big data, and this includes things like artificial intelligence or predictive analysis. Using these types of approaches can extract meaningful insights from big data and help you really dig deeper into what it is telling you. 

Collaborate Effectively with Colleagues 

Working successfully in data analysis means working effectively with a range of colleagues. This could be anything from the IT security manager to data scientists, senior managers, and CEOs. Being able to collaborate effectively not only means discovering knowledge to enhance your analysis of big data but also reporting your findings back in a way that can be turned into real-world actions. 

Continuous Updates to Corporate Cybersecurity Policies

The sad truth is that cyber threats are always evolving, and cybercriminals are always looking for new ways to target businesses. As a result of this, it is key to update not only online security policies for employers but also big data security analysis measures for analysts. This helps you to stay one step ahead of cybercriminals and keep up with the latest industry developments when reviewing big data for online security.  

What Challenges Do Data Analysts Come Across When Digging Into Big Datasets for Cybersecurity? 

The analysis of data can be useful to businesses in a number of ways, but better online security is certainly one. For this reason, data analysts who can interpret big data to draw out actionable information in this area are valuable to employers. 

The very act of analyzing data, though, can come with its own challenges in terms of online security. But what might the biggest be? 

Perhaps the best place to start for any budding data analyst is data privacy. This is especially critical when working with large, sensitive sets of data. In these circumstances, analysts must ensure they follow a company’s data privacy policies so they do not, in fact, cause any digital security issues themselves. This may include data anonymization, access controls, and encryption of datasets. 

Data protection is another major challenge when working with big data for cybersecurity. This is because big data analytics will normally involve collecting, storing, and reviewing huge amounts of sensitive information.

It is absolutely key to follow any data protection procedures at your workplace and ensure any data you are looking into remains protected from hackers. Secure data handling also feeds into this, and analysts must always ensure they handle any data they are reviewing in line with their firm’s latest governance guidelines. 

Big Data Analytics Is Critical for Actionable Online Security Insights 

It is without question that analyzing big data is an effective way for companies in all sectors to gain valuable insights into operational areas like cybersecurity. This is certainly true for firms in the finance industry, which can review data collected to inform their IT risk management policies or pick up on suspicious patterns of IT network activity. 

It takes someone with expert skills to work properly with big data in this way, and this is where data analysts come in. These trained professionals are able to work with large batches of information and use their knowledge to tease out valuable online security insights from them. Due to this and the importance of big data analysis in cybersecurity, data analysis professionals are among the most crucial parts of any modern workforce on a global scale.