If you’re in business intelligence and data analytics, you might want to consider cultivating a new title: data scientist. The change could offer a handsome return on your investment.
A recent report by the Wall Street Journal notes that, for those with the right credentials, background, and business and technical skills, pay for entry-level jobs can run $200,000 a year. That’s a pretty serious starting point.
The reason comes down to basic economics and the law of supply and demand. Many companies want data scientists and there aren’t enough to go around. First, the demand. Corporations increasingly look to intricate analysis of extremely large data sets to find patterns, trends, and indications of what is going right or wrong with operations and strategy. That will only increase as the Internet of Things expands and intelligent devices are increasingly incorporated into objects. Gartner has estimated that by the year 2020, there will be 26 billion intelligent devices sending out data that companies will collect.
But the world isn’t minting experts in data analysis as fast as companies want their services:
Going through such vast amounts of information requires a much more skilled workforce – although how large the shortfall and resulting gap are remains uncertain. In 2011, McKinsey Global Institute warned of an upcoming shortage of “140,000 to 190,000 people with deep analytic skills” and “1.5 million managers and analysts”. Gartner estimated in 2012 that only one-third of the 4.4 million IT jobs needed globally to support big data would be filled by 2015. This year, the EU said it expected upwards of a 825,000 labor shortfall by 2020.
At the highest levels of data analysis, companies hire Ph.D.s in biostatistics, computer science, statistics, and particle physics. But the university systems of the world simply can’t produce more experts quickly enough, capable of minting far fewer than 10,000 a year.
One possible answer will be to break the job apart, because it requires “a data engineer, scientist, manager, and teacher, when you add it all together,” according to Accenture Institute for High Performance Senior Research Fellow Allan Alter. “You can take that work, break it into components and create a team that can begin to get that work done.”
So, even if someone in BI or data analysis doesn’t have the doctorate required by many of the data scientist positions, they will be critical. As data scientists are focused on the more difficult and abstruse areas, people will be needed to pull together the data, prepare it, and also do layers of analysis that may not need the services of a full data scientist. If anything, the salaries for data scientists will likely have a trickle-down effect for the BI professional.
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