Data coming in from the Internet of Things and advances in cloud computing have global data storage set to grow from 45 zettabytes to 175 zettabytes by 2025. This has led to demand for hiring data analysts that has shot through the roof, hockey stick growth, in the last five years. Yes, there is lots and lots of data but what else is driving this demand for hiring data analysts?
There are plenty of data analytics programs available to sort through all of the data, and digital transformation means we don’t need hands-on humans as much, right? Machines are definitely helping analyze the data but the messiness and lack of structure to big data is prompting the need for humans to manually “tidy” the training data before it goes into the machine learning algorithm. Humans need to parse, organize and preliminarily analyze the data before it is modeled or black boxed.
Not a Data Scientist
Some of what is driving this growth in hiring data analysts is the recognition that a more expensive data scientist isn’t needed for this work. Of course, many websites and companies confuse or even equate the two roles, but the essential work the data analyst does with the data frees up the data scientist for more sophisticated work. Often firms view a successful data analyst hire as someone they can train over time to become a data scientist. It is a viable career path, but one that typically requires more formal statistical training along the way than can be learned on the job.
More Companies On-Board
In 2018 the World Economic Forum predicted 85% of companies will have adopted big data and analytics technologies by 2022. Ninety-six percent of those companies will have plans to hire permanent staff to manage and analyze their big data. As a result the role of data analysis is forecast to be one of the most in-demand jobs for at least the next five years. LinkedIn, Glassdoor and the U.S. Bureau of Labor Statistics all agree.