Is Earning a Master’s Degree in Business Intelligence Worth It?

In the late 1800s, Frederick W. Taylor—often referred to as the father of scientific management—struck upon an idea for improving efficiency in manufacturing. Observing that most manufacturing work was composed of discrete repetitive tasks, Taylor set out to study how workers went about completing these tasks and to measure the amount of time each task took. He then compiled the data to look for opportunities to improve productivity. His technique, which came to be known as time study, produced dramatic results and was soon widely copied.

Time study is an early example of business intelligence, the process of gathering and analyzing data to seek improvements in existing processes. This focus on the here-and-now distinguishes business intelligence from business analytics, which uses data to project future trends and devise forward-thinking strategies. (It should be noted that the terms are sometimes used interchangeably by those who lump the two fields together. The distinction between business intelligence and business analytics should become better established and more widely recognized as the two disciplines assume more prominent roles in business, government, NGOs, etc., as is the current trend.)

Modern business intelligence is all about data, which is why the field is exploding: the era of Big Data has surely arrived. According to IBM, we create 2.5 quintillion bytes of data every day, with data production accelerating so rapidly that 90 percent of the world’s data has been created in the last two years. The impact on business has been predictably dramatic. Forbes reports that market revenues for Big Data software and services are projected to grow at a compound annual rate of 10.48 percent through 2027, while Big Data applications and analytics are projected to grow at a compound annual rate of 15.49 percent through 2026.

All of which points to excellent prospects for business intelligence professionals. Do you need a master’s degree to succeed in this field? Is earning a master’s in business intelligence worth it? This article explores that question.

Who are typical candidates for a master’s in business intelligence?

Students pursuing the master’s in business intelligence most often studied STEM subjects in college. The Massachusetts Institute of Technology 2018-19 class profile lists the following student undergraduate majors among its business intelligence graduate students:

• Computer science
• Economics
• Engineering
• Finance
• Management
• Mathematics
• Physics
• Operations research
• Statistics

Students have an interest in and capacity for complex software, statistics, and advanced mathematics. They are problem solvers who can master a large amount of information and are not afraid to imagine innovative solutions to business challenges. They typically have accrued several years of professional experience before pursuing their graduate degree.

Note that the Master of Business Intelligence degree is not widely offered. While some institutions confer a master’s specifically in business intelligence, most schools teach the discipline as one of several subjects under the umbrella heading of IT and Management or Data Analytics, with a corresponding degree designation. Some schools offer a certificate program, and many schools offer business intelligence, or a data analytics sequence that covers both business intelligence and business analytics, as an MBA concentration.

What can you do with a master’s in business intelligence after you graduate?

Most likely you’ll be an analyst of some sort. Job titles include financial analyst, computer systems analyst, management analyst, cybersecurity analyst, operations research analyst, pricing and revenue optimization analyst… you’ve probably detected a pattern by now. Some employers simply list these jobs under the heading ‘data scientist.’

The Bureau of Labor Statistics reports job growth rates between 10 and 35 percent in the most popular fields of analytics, with average salaries ranging from $80,000 to $102,000; Payscale.com reports an average salary of $88,500.

The field is booming: according to recent Bureau of Labor Statistics data, thefastest growing occupations in the US include data scientists (36 percent growth rate), information security analysts (35 percent), and statisticians (33 percent). A recent LinkedIn search of available positions referencing business intelligence generated more than 51,000 results nationally.

By all reckonings, Big Data is one of the fastest-growing fields and should continue to be for the foreseeable future. According to Saint Joseph’s University, opportunities are spread across such diverse fields as manufacturing, defense, health care, energy, and aviation and transportation.

So is a master’s in business intelligence worth the time and effort?

There’s no doubt that Big Data is a fast-growing sector that will create lots of compelling, high-paying jobs in years to come. The question, then, is how best to position yourself to achieve your short-term and long-term career goals.

The long term is where the argument against this master’s degree is strongest. The LinkedIn Emerging Jobs Report stresses the pace at which the jobs market is changing and counsels flexibility to “future-proof” your skill set. A master’s in business intelligence may ultimately be too limiting, hindering your ability to pivot when the job market shifts, as it almost inevitably will. As LinkedIn puts it: “Some… emerging skills didn’t exist five years ago, and many professionals are not confident their current skill set will be relevant within the next 1-2 years.” The fact that relatively few schools offer a business intelligence-specific master’s suggests that institutions fear the degree may be too specific.

That said, Big Data is here to stay, and any point of entry will help you build your career in the field. Consider your interests and career goals in determining which degree best fits your needs: a master’s in business intelligence, a broader master’s in data analytics, or an MBA with a data-related concentration.

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