Business Intelligence Analyst v Data Scientist which is the better career option?

“Every company has big data in its future, and every company will eventually be in the data business.” – Thomas H. Davenport

If you are looking to compare the career paths of business intelligence analyst vs. data scientist, but are not sure what kind of skills are applicable in each profession I have compiled the similarities and differences between these occupations to help.

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% while demand for data scientists is expected to rise 16 % by 2028.

Given the average of the growth rate for all occupations is about 5%, these two different fields seem to have a better outlook. However, a business intelligence analyst does not seem to be as popular as a data scientist.

Similarities between Data Scientists and Business Intelligence Analysts

As a data scientist your understanding of the data will determine how successful your model performs and forecasts. For instance, if you are building a model to forecast regional sales. You need to know what is the most important or combination of factors that affect that regions sales. Only then can you input those factors into your model. Thus allowing your model to be able to give reasonable predictions.

A business intelligence analyst also needs to be able to understand the data. Every day, you will be flooded with business requests. No matter what you are trying to answer, business questions or key insights, you need to have a concrete understanding of data. For example, you can’t give insight into which kind of customers convert to brand loyalist without knowing the customer journey.

Differences between these professions

Nowadays, I find a lot of people called themselves as a data scientist. I think it is because it makes them sound smart. However, it is not difficult for you to figure out that most of them are just reporting the numbers without understanding why it happens. One key difference between data scientist and business intelligence analysts is how much reporting verses analyzing they are doing.

Business intelligence analyst are more likely to use descriptive data to retroactively examine trends and report what has happened. The reports are carefully planned and often presented monthly/quarterly. KPI's are often compared to find trends and other useful insights.

Data Scientist use predictive and prescriptive data to analyst possible opportunities for future decisions and growth. This analysis is often exploratory and uses visuals to represent the forecasts.