Pursuing a degree in a technical field can be very advantageous for professionals looking to advance their careers. According to the U.S. Bureau of Labor Statistics, there’s already a high concentration of workers in STEM, and that number is only projected to grow over the next decade. That means there’s going to be greater opportunities for employment — the BLS reported that computer science and information technology occupations are expected to grow by 11% between 2019 and 2029, adding over half a million new jobs.
Diving further into STEM careers, there are two specific sectors that combine business, strategy, data, and technology: data science and business analytics. Understanding the main differences between the two fields can help students decide which area of expertise they want to pursue based on current job opportunities, salary expectations, and skills needed to succeed. What is the difference between data science and business analytics? Here, we’ll discuss the raw definition of both data science and business analytics, as well as what each field brings to the table.
What is data science?
In its simplest form, data science is defined as gaining valuable insights and information out of data, according to Thinkful. It’s the way digital information is collected, interpreted, and processed in an effort to make critical business decisions. Depending on the industry it’s used in, data science can also improve a company’s growth and retention rates and enhance customer satisfaction.
Data science takes advantage of emerging technologies, which means its processes are always changing. For example, artificial intelligence uses scientific methods, algorithms, and systems to make it easier to collect and process data in a more streamlined and efficient way. Machine learning and data mining all come into play when it comes to data science.
Data science is the extraction of information by using the data science life cycle to best capture information, process it, and communicate it effectively to the appropriate party. The sourcing and management of this information plays a large role in the authenticity of data science as well. Without a clear representation and understanding of where information is coming from, data science loses its credibility.
What is business analytics?
According to OnmiSci, business analytics is the solution that uses data mining strategies and predictive analytics to assist in the analysis and transformation of information. It’s used to help business professionals make informed decisions based on trends circulating within big data. Some of the key tasks performed in business analytics roles include data organization, data mining, sequence identification, forecasting, data visualization, and overall information optimization.
Business analytics can be applied within a wide range of industries. From managing clinical information systems in health care to tracking busy hours at fast-food restaurants, business analytics are essential just about everywhere.
Data scientist vs. business analyst
Understanding what these different fields entail plays a large role in grasping what someone working in each would be responsible for. Let’s take a closer look at what defines the career path of a data scientist versus a business analyst.
What does a data scientist do?
A data scientist is responsible for evaluating certain queries to develop well-informed decisions by using raw data. These individuals source, manage, and analyze critical information via computer programs to detect extreme patterns that can relay useful information to important stakeholders in a business. Software plays a key role in the career of a data scientist because of the complexity of information — understanding how to leverage algorithms allows data scientists to properly analyze big data and make meaning out of it. According to the BLS, these scientists may also be responsible for cleaning or “scrubbing” data: removing errors and organizing data to make it easier to comprehend.
This role continues to grow in demand, according to Greg Boyd, a consulting firm director.
“As organizations begin to fully capitalize on the use of their internal data assets and examine the integration of hundreds of third-party data sources, the role of the data scientist will continue to expand in relevance,” Boyd told CIO. “In the past, the teams responsible for data were relegated to the back rooms of the IT organization, performing the critical database tasks to keep the various corporate systems fed with the data ‘fuel’ [that] allowed corporate executives to report out on operations activities and deliver financial results.”
Those interested in a career as a data scientist can expect a high wage — according to PayScale, the average salary for this role is $96,145, and that figure has the potential to rise to nearly $135,000 per year for those with considerable work experience.
What does a business analyst do?
While a data scientist clings to the initial stages of assessing raw data, a business analyst takes the data and further analyzes it to help a business improve its overall processes, software, and other products and services, according to CIO:
“Business analysts (BAs) are responsible for bridging the gap between IT and the business using data analytics to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.”
A BA is expected to understand how to work with stakeholders to help them understand data. They’re expected to engage with them to determine how this data can be used to make business decisions toward general efficiencies or painstaking processes that can add business value.
While the salary of a business analyst may be less than a data scientist, someone in this profession can still expect to earn a competitive wage. According to PayScale, a business analyst makes $68,973 per year, but can earn a salary as high as $97,000 or more.
Skills that play a major role in information systems careers
Some of the most basic skills every information systems professional needs to succeed include problem solving, management, specialized industry knowledge, computer programming, and security awareness. There are specific skills needed to gain a career as a data scientist, and business analysts also have certain proficiencies that help them thrive.
Skills needed to become a data scientist
Organizational skills and critical thinking are essential for data scientists, but more technical expertise is expected in this field. Some of the most important soft and hard skills for data scientists include communication, math, deep learning, data architecture, artificial intelligence, machine learning, and coding.
Celeste Fralick, chief data scientist at McAfee, told CIO that risk analysis, process improvement, and systems engineering are among the top essential skills needed to be a successful data scientist.
“I’ve never known an excellent data scientist without these skills,” Fralick said. “They all play hand in hand, both inwardly focused to the data scientist but outwardly to the customer. Outwardly, these are all skills that data scientists require to probe the customer about what problem they are trying to solve.”
Skills needed to become a business analyst
A successful career as a business analyst starts with having a solid foundation of both soft and hard skills. Oral and written communication skills are essential, as are organizational and technical skills that can help you assess data before passing it along to key stakeholders. Other important soft skills to have as a business analyst, according to the International Institute of Business Analysis’s 2019 Global Business Analysis Salary Survey Report, include critical thinking, leadership, emotional intelligence, and storytelling.
Beyond problem-solving, critical thinking, and decision-making, some of the top hard skills expected of business analysts include customer experience, change management, agile mindset, negotiation, and design thinking.
Reasons to get your Master of Science in Management Information Systems
The need for IT professionals is only expected to grow over the next decade. But that means there will also be a demand for professionals who can properly assess data and help business leaders make well-informed decisions. A career in business analytics shows great opportunity for the years to come, for example, as the BLS reports that the job outlook for management analysts is anticipated to grow 11% between 2019-2029.
That said, taking the next steps to further a career in business analytics or data science starts with getting a master’s degree. The University of Alabama at Birmingham’s online Master of Science in Management Information Systems program is an excellent stepping stone for students interested in pursuing a job in this growing career field. Blending the perfect mix of business, strategy, security, and leadership, this UAB program can help you develop all of the skills and knowledge needed to succeed in a wide variety of roles, such as project management, social media, IT governance, business intelligence, and data security.
While this program is designed to help IT professionals move forward in their career, that doesn’t mean your bachelor’s degree has to come from a related field. We want aspiring tech experts to pursue the MIS degree to fuel a career driven by dedication and passion. And since this master’s program is online and flexible, you can continue working in your current field and finish the transition to your new industry without committing to a four-year in-person schooling program.
Excited to learn more? Visit the MIS program page to see how a management information systems degree fits your career goals and professional interests.