What is Big Data?
Part 1 of 4
Big Data is the newest Big Buzzword, and it’s rolling across the IT landscape like the fast-paced “cloud” buzz-storm that preceded it. While the cloud has already become entrenched in our vocabulary and physical security systems, Big Data is just beginning to appear on the horizon. Given the vast amounts of unanalyzed data we collect in our industry, the tools and analytic techniques of Big Data hold out the promise of extracting more business value from our security systems than has ever been possible before.
What’s the definition of Big Data?
We’ve all been using data for a long time, usually in the form of relational databases that allow us to make queries and see the results in whatever visual form we desire. Is Big Data anything more than just a really large version of the database tools we’ve known for decades? There are several points of view on this question, and several competing definitions of what constitutes true Big Data.
First, there’s the “3 Vs” camp: volume, velocity and variety. Get enough of these three in any combination and you’re dealing with Big Data. From this point of view, there’s no real description of the technology, and it ends up sounding an awful lot like what we’ve known for years as Business Intelligence – advanced analytical and visualization techniques, but on a much larger scale.
Next, there’s a viewpoint that says the real difference that Big Data brings is the ability to understand not just large volumes of data at high velocity, but doing so with so-called “unstructured” data in real time. Think of gathering unfolding intelligence from random text on social media in order to predict the direction of the stock market. Traditional tools won’t do this for you, so you’ll inevitably be shopping for some new software technologies if that’s what you’re after.
This second camp comes close to our third way of defining Dig Big data, which focuses on the technologies needed to handle extremely large data sets that are “too large to process using traditional techniques.” That’s vague, I know, but it drives the question toward more of a “size matters” criterion, where practitioners are talking petabytes and exabytes of data as the threshold for true Big Data.
Who is using it?
Big Data techniques are now being used to provide insight into many scientific and business questions. Science has been generating massive data sets for a long time in such fields as particle physics, meteorology, genomics, and many others. For most of history, scientists have had to develop custom analytical techniques for each of these domains. Now, however, they are able to exploit the power of Big Data tools that have been forged by cloud computing and made widely available through the popularity of the open source software movement.
What are the results?
Businesses with access to rich data sets are also using these new techniques to understand complex customer behavior patterns in order to improve market share. A recent MIT study, for example, found that companies that used Big Data to their advantage were 5 percent more productive and 6 percent more profitable than their peers. In a world of narrow margins and flattened growth curves, those are impressive, meaningful gains.
How does this fit physical security?
Somewhat closer to home, we in the security industry are also part of a growing trend toward the adoption of Cyber Physical Systems (CPS) with widespread sensor networks that are producing exponentially more data every year. This vast quantity of data is useless unless it can be meaningfully analyzed to produce business value.
And there’s the rub. You need to know which problems you want to solve. And for that, as one McKinsey columnist quips, the most important tool is…drumroll…the pencil.
How can it benefit our customers?
So, if we take out our own pencils, our first question should be: What security problems could we solve for our customers if we had all the right data? If we start from this point of view – that is, what outcomes are we trying to achieve—then we won’t be lead down the path of making cool charts just for the sake of cool charts.
Think: What do our customers need?
Would understanding variations in behavior among employees help identify potential inside threats? Would the large enterprise be able to allocate security dollars more efficiently if they could see how one facility stacks up against another? Would security departments to be able to improve their own system performance if they could benchmark it against their peers?
Through this article series, we will explore these questions of business value, plus do a deep dive into the key technologies and data sources that can help us answer these questions.
Time to sharpen our pencils.