October 22, 2015 By Leslie Wiggins 4 min read

You might be wondering why securing big data is a big deal. After all, big data is just normal data, right?

Big data is indeed just data, but there are some key differences. Big data is just that — really big. There are really large quantities of it, a wide variety of data types are covered by the term and the speed at which it arrives and flows through any given environment is unique. To this end, any organization deploying a big data analytics platform needs to be prepared. The enterprise also must have thought through the different data security requirements that this will place on the traditional data landscape.

Leadership Turns Its Attention to Big Data Security

In most cases today, business leaders haven’t yet stopped to think about the security implications involved in big data analytics. But by getting ahead of this issue, you can become the power behind the throne and enable business success and growth.

The big data analytics conversation has been taking place for several years at the business level, within marketing and strategy teams as well as the IT organization. On the business side, big data analytics gripped employees’ imaginations, and teams understood how it could help take huge volumes of data from different sources and analyze it rapidly. This allowed businesses to track disease patterns, understand customer buying patterns or even uncover possible tax fraud.

On the flip side of the coin, IT has long seen the potential benefits of adopting analytics platforms such as Hadoop or NoSQL. The potential cost savings for storage alone are huge.

Businesses have spent the last few years vetting different big data platforms, putting them into nonproduction, working out the kinks and then pushing them into production. The adoption cycle has taken a while. However, it’s safe to say that big data analytics is here to stay. This brings us to the next point: Big data projects are fueled and powered by sensitive data — patient information, customer data, personally identifiable information (PII), etc.

Read the complete e-book: Top tips for securing big data environments

Are You Prepared for the Worst?

This is what makes big data, and the big insights it has the power to reveal, a potential big exposure. It’s time for security teams to take a close look at what their business counterparts are doing or are planning to do in the big data analytics arena so they can start to prepare — particularly when you take the following into account:

With the right level of planning, security teams can do a lot to enable the business to safely leverage big data analytics and all the benefits it has to offer. In some ways, securing big data carries the same risks as securing regular data: There are compliance requirements that must be met, potential costs of data breaches to consider and a brand reputation at stake.

Yet big data analytics also introduces new challenges: There are new users accessing, manipulating and possibly sharing the sensitive data fueling the platform. Given the nature of the data flowing through big data analytics platforms, this creates a particularly juicy target for cybercriminals. The target is also often low-hanging fruit because big data platforms don’t typically provide much in the way of comprehensive or sophisticated security capabilities.

Big Data Can Be Secured

But don’t lose heart! There is a way to plan for and successfully secure big data. As with any security initiative, the first important thing to recognize is that big data platforms don’t exist in a vacuum; they are or will soon become part of an integrated environment. You need to think of how to secure the data sources that will feed the big data platform, as well as how to protect the sources and the data itself. You need to assess vulnerabilities among your various data repositories to harden that part of your environment.

You also need to be able to monitor data activity across the sources, the big data platform and users. The platform should support real-time alerts or even block access in real time if suspicious behavior occurs. And last but not least, you need to make sure your big data security approach is consistent and integrated with the approach you use across the rest of your enterprise. If it’s not, you provide the bad guys a loophole they might be able to exploit.

By planning ahead and being prepared for the introduction of big data analytics in your organization, you can become the power behind the business throne. You’ll be able to help the business meet its objectives — securely.

To learn more download the e-book: Top tips for securing big data environments

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