With ever-growing technological innovations, the complexity of IT networks has risen sharply. Mobile devices, tablets, and wearable technology are generating huge amounts of data in real time that is getting exposed to cybercriminals. There are over 23 billion IoT devices connected to the internet today, which have created larger cracks for cyber attackers to exploit.

Information and business data are very important for any organization – they are increasingly taking note of the value of this data for their success in the current economy. This overwhelming reliance on information and data to make important decisions also requires protection of company and customer data. Organizations should implement strategies and may need to invest in testing security against penetration so that even the most sophisticated attacks can be foiled.

Today, the increase of cyber-attacks in terms of volume and complexity has made the traditional tools and infrastructure redundant. To combat the growing number of cyber-attacks, big data analytics is showing its immense potential and organizations are increasingly banking on it. According to a recent US Government survey, MeriTalk, 90% of respondents said they observed a decline in security breaches.

Big data analytics refers to the process of evaluating large data sets with an aim to uncover hidden patterns, intricate correlations, market trends, consumer preferences, and other useful information. It uses advanced statistical and data science models for speed detection, while a real-time stream processing enables rapid threat analysis. As a significant technological push, organizations have finally reached a point where intelligent algorithms and large-scale data processing are helping them secure business data. These tools operate in real time and generate a small number of security alerts as per their severity level. These alerts are further augmented with additional forensic details for quick detection and mitigation of cyber breaches.