You’ve got your accounting degree, but what now? Supplementing it with experience in data analytics can net you a higher salary than simply being a CPA. And the push to weave cognitive technologies into auditing processes could give you the chance to work with artificial intelligence, and even drones.
Data analytics is a discipline that takes raw data and then uses that information in making decisions. It’s used in manufacturing for efficiency on production lines; and in online commerce to determine sales of goods to a specific group of customers. For auditing, data analytics would be used in identifying patterns, trends, and risks.
An example of a relevant role is data scientist, whose livelihood hinges on the ability to analyze and extract practical knowledge from those figures.
Speaking of numbers that matter, a data scientist in the U.S. takes home an average annual salary of $113,436, according to Glassdoor. By comparison, a CPA earns an average $58,431.
The Massachusetts Institute of Technology offers a certificate in big data and social analytics, and is one of several high-profile American institutions that offer training in analyzing and interpreting data. MIT’s program takes a hard look at what it calls social physics — “statistics meets big data to understand people.”
For CPAs, data analytics offers the opportunity to work on the cutting edge of technological innovation, and accounting and auditing firms have taken notice.
Deloitte CEO Cathy Engelbert was quoted by Accounting Today as saying earlier this week that she expects accounting and auditing to progress exponentially in that direction, and there would be more changes in the next five or six years than there have been in the past three decades.
Technologies being used at Deloitte include robotics, allowing for the automation of compiling data into templates; and drones, which might be used to take inventory at a farm by flying over a grain silo and capturing images from above.
KPMG’s website maps out the company’s mission to augment the auditing process through artificial intelligence by using machines that are able to perceive, reason, and learn the way a human would.
But no matter what role AI might play in the future of data analytics, the need for human discretion will remain, Engelbert said.