Large organizations and enterprises are embracing big data like never before. In fact, New Vantage Partners revealed in 2019 that around 97.2% of companies are investing in both big data, and artificial intelligence.
In today’s business environment, big data isn’t even too big for small and medium-sized organizations. The global big data market is forecasted to grow to 103 billion US dollars by 2027, more than double its expected market size in 2018, as more technologies are built to help businesses make better use of big data.
Big data today is needed to reveal hidden patterns, market trends, customer preferences and other meaningful business insights.
But with this massive increase in data processing, storing and consumption comes increased security concerns. Organizations must ensure that not only is this data protected from third-party threats, but that they manage and use it in a way that complies with regulatory compliance requirements.
Big data security is a crucial aspect for any business that wants to leverage big data’s potential while at the same time effectively mitigating the risks that come with it.
Big data security: Definition
Big data security is a collective term for all of the measures and tools used to protect a company’s big data analytic tools from cyber attacks, third-party theft and other malicious activities targeting the organization’s data.
Big data security aims to protect a company’s data in two phases. Firstly when it is in transit from one location on the network to another, and secondly when it is in storage - where it can be stolen or held hostage by malicious threats while it is resting on cloud or on-premise servers.
The aim of big data security is to protect data from malicious cyber attacks. This becomes increasingly important when businesses store information that is sensitive (such as personally identifiable information), like customer information, contact details and credit card numbers.
Companies that process and store sensitive data must comply with regulatory requirements such as the EU’s General Data Protection Regulation (GDPR), HIPAA for organizations in the healthcare industry or the California Consumer Privacy Act (CCPA).
Why big data security is essential
With an increase in big data, a company’s overall attack surface grows. But loss of data can result in serious consequences for a business that suffers it, such as financial repercussions, damages to brand reputation, as well as compliance fines and sanctions.
Big data security aims at mitigating those risks and keeping unauthorized users out of a company’s network through improved data visibility and classification, firewalls, user authentication, end-user training and data protection.
A big data security strategy will provide a business with protection against cyber attacks, thefts and other malicious activities that could harm valuable data.
What tools and strategies are included in big data security?
Big data is a strategy that, when implemented, is made up of a wide range of processes and tools to protect a company’s big data analytic platforms. Here are some of the most common, and effective, big data security measures.
Encryption:
Data is completely useless to malicious hackers if they don’t have the key to unlock the data. For that reason, many organizations implement encryption into their big data security processes so that, even if it’s stolen, cyber attackers cannot access the information.
Data classification:
Through the process of classifying and organizing data based on a set of clearly defined characteristics, data classification helps businesses to easily find certain pieces of sensitive data, and identify how each piece of data should be stored, managed, used and shared depending on which regulations it must comply with.
Firewall:
Organizations are able to better prevent malicious attacks before they happen by using a firewall to filter traffic when it both enters and leaves the company’s network.
End-user training:
In the large majority of cases, big data is compromised as a result of a successful phishing attack on an unknowing employee. End-user training sets your employees up to know what a malicious attack looks like, identify possible threats and, as a result, avoid falling prey to them.
Data visibility:
Organizations cannot protect their data if they can’t see it. Data discovery software scans an organization’s entire network, finding and identifying where both structures and unstructured data resides. This gives businesses real-time insight into their data inventory, so they can improve their data protection processes to protect it.
Big data security - Next steps
Looking for a way to further protect your company’s big data?
Request a demo today. We’ve created a unique attack surface management platform that gives businesses complete visibility into the data they store across their network, so they can implement a data protection strategy that better protects their data.
