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Data Science vs. Business Intelligence: What's the Difference?

A businesswoman using a stylus on a monitor to point to various charts		Big data is the next big thing — and trained professionals who know how to squeeze commercially useful information out of data are in high demand. Companies in industries of all kinds are increasingly relying on business intelligence analysts and data scientists to give them an edge over their competitors and help boost profits.

Business analysts and data scientists work together to turn raw data into useful information. They fill different, but related, roles. Both types of professionals are highly sought after, but which job pays more? While both positions are well paid, a career in Business Intelligence analysis will get you a six-figure salary much sooner, since it requires less formal experience than a career in data science.

Business Intelligence Analyst vs. Data Scientist: Understanding the Difference

Data scientists and Business Intelligence (BI) analysts have different roles within an organization; usually, a company needs both types of professionals to really optimize its use of data. In a nutshell, BI analysts focus on interpreting past data, while data scientists extrapolate on past data to make predictions for the future. Data scientists help companies mitigate the uncertainty of the future by giving them valuable information about projected sales and making general predictions of future performance.

BI analysts, on the other hand, interpret past trends. These big data professionals perform more meticulous, plan-based work; they slowly put together the pieces of the data puzzle to arrive at concrete truths, rather than making guesses based on probability. Both types of professionals are necessary to maintain a company’s financial health.

Data Scientists and Business Intelligence Analysts Are in Demand

Data scientists and BI analysts share great job prospects, since companies are struggling to fill positions in these fields. According to the McKinsey Global Institute, the U.S. currently labors under a shortage of 140,000 to 190,000 professionals with specific analytical expertise. A Burtch Works survey said that 89 percent of data scientists on LinkedIn were contacted about job opportunities monthly, and 25 percent received weekly job offers through the site.

The situation is expected to become far more serious over the next few years. By 2018, the McKinsey Global Institute predicts that U.S. industries will add four million more big data positions, and those positions will all need to be filled with professions who possess quantitative and analytical skills. By that year, the country can expect a shortfall of 1.5 million analysts and managers who can analyze big data and make sound business decisions based on that analysis.

What does it take to build a career in big data? In addition to an advanced degree in mathematics, statistics, computer science, engineering, or business intelligence, desirable job candidates must have good business sense and strong communication skills. Big data job prospects are already great even if you’re a new graduate just entering the field, but once you have a few years of experience under your belt, you can expect your job prospects to increase exponentially.

A man points to a chart projected on a wall, while two colleagues look on		Earn a Six-Figure Salary Sooner in BI Analysis

Starting salaries for data scientists average about $80,000, but workers with at least nine years of experience in the field can command around $150,000. However, the barrier to entry into data science is much higher than the barrier into business intelligence analysis. Aspiring data scientists need at least a doctoral degree in a related field, meaning these professionals spend more time in school and accumulate more student loan debt before they are able to enter the work force.

That’s why a career in BI analysis is arguably the more lucrative field. If you’re looking to get into business intelligence analysis, you need only a business intelligence master’s to enter the field. That makes a career in BI analysis a lot cheaper to prepare for, both in terms of tuition spent and the time taken out of the workforce to earn the degree. Demand for BI analysts is high enough that there should be no doubt about your job prospects after graduation, especially if you have a good head for business and good people skills.

If you’re considering a career in BI analysis, you can expect to command a starting salary comparable to that of a fledgling data scientist. New BI analysts earn a starting salary of about $87,000, while those who are able to move into managerial roles make nearly double.

Companies in all industries are desperate to hire professionals with the quantitative and analytical skills to wrest useful information from huge amounts of raw data. If you’re considering entering a big-data-related field but aren’t sure whether data science or BI analysis is for you, ask yourself just how much time you want to spend in school and how much student loan debt is acceptable. Thanks to high salaries and a lower barrier to entry, BI analysis is often the more lucrative career.

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