Hand, Magnifying Glass, Earth, Globe

When we look at the techniques used in Big Data Analytics, it is seen that methods are used. On the other hand, data analysis tools are often used by analysts, researchers, and engineers by companies to access business data efficiently. The complex, extensive data analytics process often includes complex applications such as statistical algorithms and, if any, analysis and predictive models driven by high–power computing systems, high–performance analytical systems, and proprietary software.

Another purpose of using Big Data Analytics is to discover relevant information (consumer preferences, market trends, unknown correlations) that can help a business or institution increase operational efficiency, improve customer service, develop and implement more effective marketing strategies, find new revenue opportunities and gain a more competitive advantage over competitors.

Using Big Data Analytics in Cyber ​​Security

For a long time, Small & Medium Businesses (SMBs) were not considered a possible target for sophisticated Cyberattacks. But now, both the place of SMEs in procurement processes and their weight in economic activities have made them the target of Cyberattacks. In short, company size or smallness does not matter for attacks anymore.

The companies exposed to these primarily targeted attacks are those that do not generally use robust encryption technology and are focused on doing more business online through cloud services. On the other hand, with the increasing number and complexity of Cyberattacks and the fact that all kinds of companies are now the target, “traditional” tools and methods can no longer provide adequate protection. At this point, Big Data Analytics comes into play and promises a new potential in terms of Cybersecurity solutions.

Big Data and Cyber ​​Security

On the other hand, entrepreneurs are beginning to realize that the importance of this data for business success in the market is increasing. Now mobile devices and wearable technologies are helping businesses collect massive amounts of data about their users. It’s here that security and privacy seem to be getting worrisome. In this context, entrepreneurs continue to look for ways to keep sensitive business data out of reach of cyber attackers.

The use of Big Data Analytics and Machine Learning enables businesses to perform seamless analyses of the collected information. As a result, the study results can give clues about possible threats to the company’s integrity.

In this context, Big Data is seen as both a threat and an opportunity for companies and researchers. Indeed, as the increased volume of data whets the appetite of cyber–attackers, Big Data Analytics stores large amounts of data, making it easier to conduct data analysis that helps analysts examine, observe and detect irregularities within a network. On the other hand, security–related information from Big Data Analytics shortens the time needed to detect and fix a problem. This framework helps Cybersecurity analysts to predict the possibility of intrusion and attack while making it easier to protect against attacks.

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