The modern enterprise has a complex and complicated IT structure. In most instances, there is a mix of on-premise solutions for computing or storage, coupled with cloud-based solutions that help alleviate the in-house burden. To ensure that all entities work congruently and that information flows seamlessly between the entities, unifying data connections are in place.
While applications are distinct in that they can be categorized as either running off-premise or locally, the Internet of Things (IoT) only serves to convolute the process. Now, almost every device can be connected to another in some way, meaning that the web of data points is infinitely wider than it ever was before. As a result, it is also weakened and more vulnerable to attack. With such breadth and scope of influence, there are now multiple entry points through which an effort of malintent could attack. We see this directly in the form of data breaches when large enterprise networks are brought down by the actions of just a handful of people or even just one determined hacker.
As such, it comes as no surprise that the enterprise cyber security sector is rapidly rising. In fact, Forbes predicts that this industry will continue to rise at a Compound Annual Growth Rate (CAGR) of 9.8% over the next few years, reaching a worth of $170 billion by 2020. Company leaders around the world realize the importance of investing in proven security solutions to keep their most important asset — their data and the people who work with it — as safeguarded as possible.
While the need is at an all-time high, the good news is that with every data breach or insecurity identified, these products grow stronger and more sophisticated, in most cases able to detect negative action before it snowballs into catastrophe. Still, a single solution is rarely powerful enough to sufficiently cover an entire enterprise. Rather, a deeper and more comprehensive approach is often preferred, beginning at the outer edge of the network and moving inward, becoming more focused and intricate at the nucleus of business.
While these solutions might be a company‘s only defense against would-be data intruders, the reality is that their integration carries with it a few considerations. Chiefly, the more advanced the security software, the more training personnel required to get in-house teams up to speed on its use, and the more management-level employees needed to oversee daily implementation. As this trend continues, more and more corporations are finding that, while of utmost importance, data security is demanding a substantial percentage of the IT department’s time and resources, leaving little for other equally vital areas of concern.
The result? Most companies are forced to weigh whether or not to invest in additional security resources against the actual threat they feel from the outside. If they’re comfortable and confident that the risk level is low, so too is their focus on these resources. While this might be an effective game to play at the onset, it’s one that could turn sour at any given minute. As such, a more strategic approach to security investments must take place, and that’s where big data comes in.
The Role of Big Data in Security Software Integration
For all of the advantages and insights Big Data affords us, it is not without its drawbacks. The top point of contention to remember is that the more vast the data lake, the more opportunity exists for manipulation. This is because the said lake is comprised of myriad data points that work as individual units, from in-house computer systems to smart devices and wireless technology solutions that work together to power the company forward as a collective force. As each data point could, at any time, turn into an entry point, it makes it infinitely more difficult for leaders to pinpoint where the breach occurred.
In the same vein, it also makes it harder for them to identify the origins of a data threat. This issue becomes even more exacerbated when you consider that while, just a few years ago, critical company data was stored in one centralized database, that information could now be spread out over a handful of databases, each with its own form of authorization and access. As such, when someone logs into the system, how can you tell if it is legitimate and approved, automated from an interface, or the first step in a detrimental hacking?
The answer lies in the fact that these systems can also gather, store and analyze an incredible amount of information from the IT environment. In the technology industry, this is a feature known as telemetry. From server activity to traffic on the network, user statistics and more, the eyes on security software are always on, allowing business leaders to get a firsthand, real-time look at how operations are performing. That said, if there is a security threat taking place, the solution will likely capture it in a format that is instantly viewable and actionable. These security analytics can play an essential role in helping administrators determine whether or not a network is under attack.
The Critical Role of Advanced Analytics
On its own, however, data is simply a collection of facts. It is the connections between these facts that gives context and meaning to the information gathered in the Big Data process. At any time, there are multiple connections being forged within a data lake. Determining whether or not these connections are valid requires advanced analytics.
The most forward-facing analytics solutions within this sphere work by first collecting the information, then storing it in a central location, where it is then mined for any patterns or activities that appear erratic, don’t fit the mold or might signal foul play. Depending on the program, the software can handle the launch of corrective counteraction immediately or signal to higher authorities that next steps need to be made to keep the data enterprise safe.
Performing these actions within a big data environment is preferred, as it allows users to maintain control and also ensures against costly employee downtime. The big-picture perspective also allows enterprise leaders to more accurately detect global threats before they pervade smaller-scale systems. One preferred approach is to run security software via cluster technology, the most notable solution being the Hadoop Distributed File System (HDFS), which analyzes application logs to track activity at every level.
A Look Forward: The Future of Data Security
Ultimately, as technology continues to sophisticate so too will it open more doors than ever before — and create new, unwelcome entries along the way. Keeping your company secure will require staying up-to-date on the latest trends, developments, and software releases designed to keep your data where it belongs. Moving forward, enterprises will continue to prioritize big data for the major role it plays in helping prevent and mitigate threats.
Yes, a data lake can be one of the most confusing and overwhelming aspects of IT. Yet, it also means there are multiple working parts coming together to meet a shared and common goal. Leveraging your analytical insights to create a stronger data network is the ideal next step after integration. Here again, big data is changing the way we operate as organizations. In short, it’s directly affecting how we learn about our customers, streamline our processes, evaluate partnerships and yes, keep every touch point and connection as safe as possible.
