Big Data Management and Its Security Challenges

The benefits of big data, like always, keep on increasing. Individuals, organizations, government institutions, etc., that are eyeing a faster throughput, need large collections of data for predictive analytics. However, with growing volume and variety of data, challenges related to its management and security are being faced.

Managing thousands of servers and hundreds of terabytes of data is a significant consideration. Big data that is poorly governed and protected often ends up being a liability for the organization instead of being the most powerful asset. In order to deliver and sustainable and consistent results, one needs to find top-notch management and security solutions.

Big data is different from data warehousing and data mining, although one can’t deny that there are few similarities. The thing about big data is it doesn’t have the one-to-one data storage framework, so there is no single server involved. Big data storage relies on virtualization architecture, which involves distributed networks of large data environments, often spread across different geographical locations. Content is derived from various sources and archived as a single global resource.

Now the challenge is that a complex environment of massive data becomes too much to process through hundreds of pre-built connectors. Also, understanding and monitoring big data clusters require highly efficient security engineers who will be examining and monitoring files day and night for their optimal upkeep. But there are several solutions:

When data is analyzed and used for crucial developmental activities, its quality and safety is a serious issue. Large sets of consolidated data become the target of various criminal groups that can achieve bigger payoffs from a single attack. Of course when data will be big, breaches will be big tool.

Any compromise in data quality will affect correct decision making and might lead to increased expenses. Accurate and correct data enable professionals in taking smart decisions, promote innovation, reduce costs, and accelerate growth. Should the information lose its quality and authenticity, it will negatively affect every other entity that’s even least associated.

Security concerns for big data arise due to fallacy in two areas: infrastructure and technology. When a large number of distributed servers comes into factor, it becomes too complicated for engineers to ensure safety to all the servers at the same time. Hence, some systems are left vulnerable. Coming to technology, many companies still rely on the traditional encryption approaches that often fail to secure the big data environment. Fortunately, there are several solutions:

The exponential growth in big data is a good sign whatsoever. The best practices for working with big data is still in its growing stage, While the innovation cycle is running at its full speed, current firewall security systems such as Bitdefender offer an excellent protection for all kinds of big data privacy. However, there must be ongoing monitoring and audits to ensure an optimal integrity, confidentiality, and availability of big data.