It’s no secret that over the last year, companies have adopted and deployed big data architectures and analytics like never before. They’ve caught the big data bug and they’re using the insights gleaned from that data to anticipate, plan and react to situations in real-time. If your organization is doing this, then you’ve likely seen great results, but have you ever stopped to think about how secure your data and, in turn, your decisions are?
Decisions, changes and new technologies, like data analytics, are being implemented so quickly that legacy processes simply can’t keep up. The gap between new and legacy systems is often just wide enough for a security risk to slip through. Once these risks penetrate the gap, they’re moving at the speed of light themselves, diving into data and jumping back out before businesses even know what hit them. You don’t have to look far to see this happening – from recent and high-profile data breaches to stolen financial information, we’ve seen it all.
Herein lies our dilemma. How can we take full advantage of the volume, velocity and variety of data available today while ensuring the data remains secure?
Out with the old, in with the new
To make changes of any kind, you need to know what you’re working with. For the purposes of this exercise, that means knowing where your data is stored. Strike up a conversation with your security team and they’ll likely tell you that it lives in silos. Each business function, team, person, etc. has its own data silo and the security tools that are in place are responsible for protecting the perimeter of said silo.
It’s the typical “burglar alarm” approach to security, but we’re not dealing with old-school burglars. Today, these guys are savvy. From 17-year-olds who can write code capable of breaking through corporate strongholds to hacker groups bent on causing mayhem, it is absolutely critical that more than just the perimeter is secured. Once that perimeter is breached, the floodgates open and entrants gain access to everything from financial data to confidential emails, supply chain routes, disparate databases and more. Cue the chaos and a lot of late night phone calls.
So what’s the fix?
Data centralization: The new norm?
In order to best secure your data, it needs to be centralized.
As I mentioned on stage at Gigaom’s Structure Data conference in March, companies can be wary of taking this approach. They believe that housing their data in one, centralized repository actually makes them a bigger target for hackers. In fact, it does quite the opposite and it should be the new norm for all companies that are trying to take utmost advantage of their data. Let me explain.
By breaking down the data silos and centralizing your data, it’s possible to increase visibility across your organization, which is critical for those real-time insights and decisions that drive business success and establish competitive edge.
Data centralization enables business to protect each separate data point and element. Each data point can be tagged with specific attributes that regulate access by user, location, device, etc. That data can then be tracked as it travels in and out of your organization with the pre-set attributes attached to it. It’s like putting a password-protected GPS on your data.
Keep in mind that implementing this new process of data tagging and centralization isn’t an overnight process. It takes time and close collaboration between IT and the business units. Security teams need to work closely with employees across the business to provide the tools they need to publish and consume data while also ensuring it is protected, audited and logged. This collaboration is crucial because it is the employees who truly understand the value and the necessary security classification for each data point, file or folder.
Despite the work involved, data centralization has real and tangible benefits for the business. Businesses who adopt these models find the outcomes to be extremely valuable. It allows them to work closely with employees and break down organizational hierarchies, which leads to greater collaboration across the organization, and, at the same time, secures data and reduces overall risk.
Peter Guerra, a principal in Booz Allen Hamilton’s Strategic Innovation Group, is responsible for leading the day-to-day operations of one of the firm’s largest data science teams. Follow him on Twitter @petrguerra.