Finance is one of many sectors that's rapidly evolving as the use of big data becomes more mainstream. The industry is becoming more dynamic and technology-driven, and it's important that the world's banking leaders do what they can to keep up.
Banking is a high-stakes game, as institutions are handling massive amounts of money for their clients, frequently making life-changing decisions. They can't afford to rely on guesswork that might lead to catastrophic errors. They must employ more data to improve the way they hire new staff, use new technologies and advise the world about their money.
According to The Wall Street Journal, financial heavyweights have come around to accept this idea. The newspaper states that today, every finance professional needs a degree in big data. Ideally, that sounds wonderful, but in actuality, it's difficult to make it happen. William Fuessler, global financial strategy and transformation leader for IBM Global Business Services, says he's worried about the future.
"Unfortunately, the skills needed to use big data are scarce," Fuessler stated. "In the current business world, there aren't very many data scientists who both know how to use technologies like Hadoop and have the business savvy to analyze data and ask the right questions that generate clear choices."
A labor shortage
Companies everywhere are worried that their data analytics skills aren't up to par. The Wall Street Journal found that according to a recent Booz Allen Hamilton survey, only 18 percent of managers of federal departments say they have the capabilities they'd like. This skills shortage isn't by choice - the problem is that organizations simply can't find the talent they'd like.
The gap is growing fast. According to data from McKinsey and Company, there will be up to 190,000 unfilled data scientist jobs in the United States by 2018. There will also be a need for 1.5 million managers who can apply analytical skills.
Working with big data is a multi-faceted challenge. First, one has to know how to collect information - which sources are reliable and which aren't. Then, one needs to ensure data quality, going through massive clusters of files to trim any potential errors, be they human or technical. Finally, there's the matter of actually processing the data, making sense of it and taking action.
These are all new skills, and while people are working hard to pick them up quickly, it will be difficult for the labor force to keep up with changing technology. In finance, it's absolutely essential that they do.
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