There’s a lot of hype around data scientists today, but the reality is that many companies are still in great need of data analysts, too. Data analysts play a key role in helping business users keep their eye on the ball and solve day-to-day problems.
In many ways, they can complement the work of data scientists, but they’re also important — even critical — when companies don’t have a data science program. It’s useful to consider the data scientist vs. data analyst differences so enterprises can build the right team and individuals can hone the most appropriate skills. Data analysts place an emphasis on inspecting and analyzing data [and] creating reports, while data scientists focus on experiments, research and machine learning,” said Ji Li, data science director at Clara Analytics, which provides an AI platform for the commercial insurance industry.
Author: George Lawton
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