The need for speed, part 1: Big data analytics and flying blind
Big data and the need for speed
If CIOs and CFOs wholeheartedly agree on just one thing, it’s the value of in-depth data analyses delivered at the speed of thought. Being able to reduce the analysis of billions of records—from a process that once took hours to one that now takes seconds or even fractions of a second—is the promise of “big data” and the future of IT.
Of course, it’s easy to talk up the benefits of real-time analysis, but actually building the infrastructure to deliver it is much more complicated. It’s a challenge testing CIOs and CFOs the world over—and it’s vitally important.
It’s no overstatement to say that having the right business-analytics solution is as essential to an enterprise’s health as air and water are to human life. Simply put: you can’t live without it.
Put it this way: if pilots flew planes the way most corporate executives run their businesses, they wouldn’t know they’d taken off until well after reaching 10,000 feet and the seat-belt sign had come off.
The larger and more sophisticated the organization, the more data must be processed before anyone can see where it’s headed. Comprehensive cost calculations at a large, complex company can easily take most of a day to execute.
And that’s under normal conditions. Introduce a stock-market crash, a supply-chain interruption, or a manufacturing snafu, and executives are flying blind at full throttle.
Knowledge is power—and not having it when you need it most is a CFO’s worst nightmare. With millions at risk every minute, the lack of timely analytics can lead to logistical, manufacturing, and financial disaster in less time than it takes to pull a full report.
As we all know, the data exists. Modern IT makes it possible to collect staggering amounts of structured and unstructured information. Since the 1980s, the world’s capacity to store data per person has roughly doubled every 40 months. By 2012, some 2.5 quintillion bytes were created daily.
But turning those vast repositories into usable intelligence is no small feat. The key is to stop simply collecting data and start connecting with it in meaningful ways that enhance critical decision-making—by putting the right analytics infrastructure in place.
In part 2, I will outline just such a solution…