There are nearly 15,000 petabytes of data on the internet right now (there may be more than 15,000 by the time you read this article), and that data deluge grows by 70 terabytes every second.
To put that in perspective, streaming the latest episode of Game of Thrones probably required about three gigabytes of data. Trying to consume all the data currently stored online would be the equivalent of five billion people downloading the latest Game of Thrones episode at the same time.
But that’s not how online data really works.
One episode of a TV show is a tiny drop in the vast ocean of online data. Much of that data—those 70 new terabytes created every second—is generated by and for businesses as they go about their day-to-day work.
Somehow, all of this data needs to be understood.
During an age of less internet connectivity and fewer people online, it was possible for talented data analysts to make sense of the information flooding into their systems on their own. But today, as Oracle CEO Mark Hurd has said, “Whether you’re looking at information on employees, customers, or whatever it may be, the amount of data that companies now have is beyond the ability for even the most sophisticated data scientists to take advantage of.”
That’s where big data comes into play. Big data talent is more important than ever to modern enterprises. The best big data experts now have access to advanced artificial intelligence and machine learning technologies that can help make sense of the data deluge on a real-time basis. These capabilities allow big data experts to move beyond super scaled number crunching, letting them deploy their intelligence, creativity, and perception to find actionable benefits among the billions of bits and bytes flowing through their employers’ systems.
During his Oracle OpenWorld 2018 keynote, Hurd highlighted the impossibility of manual analysis at scale and went on to point out that this impossibility is, “not true of machine learning. Further, Hurd also noted, “The opportunity to turn all that data into knowledge…[into] information that helps you sell more, [or into] information that helps you save more—AI will affect both.”
This ability to transform torrents of data into actionable business strategies can apply to many of a business’ core operational functions, including human capital management. Hurd made this connection at Oracle OpenWorld 2018 as well, noting, “35 percent of a recruiter’s day is spent sourcing and processing candidates…the ability to know whether a GPA matters, whether a major matters, whether your extracurricular activities in school matter…it’s very difficult to harness all of that data information. Not true when AI is applied.”
Recruiting departments can put big data experts to work for their cause. An analyst working for an enterprise with thousands of employees could save their employer millions of dollars by employing these technologies. By using Oracle HCM Cloud to gather and analyze data throughout the recruiting process, businesses can reduce turnover and improve the quality of hires.
Big data is more than a buzzword. Top talent can achieve measurable results for a wide range of businesses, including manufacturing, healthcare, and retail. You can see many benefits of big data on Oracle’s Big Data Use Cases page. You can also see real results big data experts achieved while working with Oracle Big Data Cloud on the Success Stories database. Big data experts have utilized Oracle Big Data Cloud to (among other things):
- Speed analytics to get actionable intelligence for GE Digital
- Help CERN run the Large Hadron Collider and understand the universe
- Help Wiggle create data-driven performance solutions for athletes
Does your organization have big data experts? If it doesn’t, finding them should be a matter of when, and not if. Having talent who can turn your organization’s flood of information into real operational results can make a huge difference in business performance and on the bottom line.