Big Data is about huge amounts of heterogeneous and fast incoming digital information that can’t be processed with traditional tools. It is characterized by 3V – Volume (the amount of data), Variety (the number of data types), and Velocity (data processing speed).
As now the data amount being collected continues to rapidly grow, the necessity in Big Data highly increases. Just recently only such organizations as government agencies, large enterprises and corporations could afford infrastructure for data storage and analysis.
Today, as technologies become more accessible, Big Data uncovers more benefits, more use cases, and more industries to be applied in.
Big Data software can provide companies with a huge competitive advantage, enabling them to receive in-depth customer data, improve personalization, marketing and CEM (customer experience management), define and eliminate corporate inefficiencies, and much more.
The results may be as follow: better company performance, risk and error minimization, and increased sales.
However, when dealing with Big Data, businesses face many challenges that include capturing large data amounts from various sources, data secure storage, smart analysis, and visualization. And here Big Data security takes the center stage.
Big Data security challenges
Big Data vulnerabilities are defined by the variety of sources and formats of data, large data amounts, a streaming data collection nature, and the need to transfer data between distributed cloud infrastructures.
In other words, the very attributes that actually determine Big Data concept are the factors that affect data vulnerability.
There are various Big Data security challenges companies have to solve. Data leaks, cyber attacks, information use for not legitimate purposes, and many others. Large data sets, including financial and private data, are a tempting goal for cyber attackers.
The consequences of data repository breach can be damaging for the affected institutions. Imagine how a company may suffer in the result of stealing trade secrets, user personal information, customer and employee data!
And the higher the value of data is, the more devastating the effect. So, banking and financial organizations, government entities, and healthcare providers are the first who should pay special attention to Big Data security.
Thus, companies need to focus on the encryption of large data volumes, prevention of data leaks, and protection of corporate information assets. Meanwhile, Big Data security solutions shouldn’t affect the system’s performance and lead to delays.