While no one has an exact figure, one popular estimate puts the amount of data generated at 2.5 quintillion bytes, each and every day. Even excluding cat videos on Facebook, that’s an incomprehensible amount of data, with higher volumes inevitably ahead.
Data has been described as the oil of the modern economy, as it powers virtually every business model. Companies spend huge amounts of money to gather, organize, and extract value from information in all of its forms.
But our familiar approach to data management is nearing its theoretical limit. The challenge? Humans. We’re showing clear signs of not being up to the challenge on our current course.
Behind any large organization are cadres of specialists who manage data contained in highly structured databases. The mission of these database administrators—or DBAs, as they’re commonly known—is to keep the data flowing and to protect it against inappropriate use.
The problem? Humans, despite their best intentions, are fallible. And the consequences of inadvertent database administration errors can be dire.
A failure to patch a database vulnerability promptly can result in a tragic security breach. Misconfiguring redundancy settings means a business-critical application can go down and stay down. Throwing more people at the problem can make the problem, well, worse.
Recently, Larry Ellison announced that Oracle will soon be offering the industry’s first autonomous database. It will use machine learning to be self-patching, self-protecting, and self-optimizing. Given that Oracle is a database leader, its announcement is a natural and logical progression.
The industry reaction was, well, curious to say the least. Is this about putting DBAs out of business? Hardly.
With commercial aircraft, we’ve used autonomous copilots for years. Why? Mostly the same reason: Humans are fallible and sometimes the consequences of their mistakes are dire. Humans must always be in charge, but we all benefit from smarter, autonomous systems. I, for one, still want human pilots in the cockpit when I’m a passenger.
Likewise, when it comes to managing ever-increasing data volumes and protecting against ever-increasing risks, we can make a strong case for autonomous databases supported by intelligent people who keep an eye on things on our behalf. Humans performing manual tasks is not a scalable data management model. DBAs ideally would focus on helping the business use its data more effectively, versus simply keeping the systems running.
Not Merely a Cost Play
Some will argue for autonomous databases on the grounds of cost savings—i.e., spending less to get more value. While those savings are real, I think there’s something more important—an increased level of risk avoidance at a time when the stakes are rising.
Just one recent example is the European Union’s General Data Protection Regulation, due to go into effect in May 2018. Fines for noncompliance can be as much as 4% of a company’s annual revenue.
And we’re not even going to talk about the Equifax breach, OK?
New technologies are often introduced when there’s a clear and present need. Autonomous databases are no exception. Our journey in gathering ever-increasing amounts of data creates both enormous value and risk.
And having an autonomous copilot along for the flight makes obvious sense.
Chuck Hollis is senior vice president for converged infrastructure at Oracle.
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