With over 400 million terabytes of data being created every day, the world is flooded with information. Businesses rely on data analysis professionals to manage digital data with precision, insight, and integrity. Companies and organizations across every sector collect, track, and analyze data regularly to assess progress and determine strategies to function more efficiently.
These data experts are generally trained in either data science or business analytics. But what sets these two fields apart, and how are they similar?
While there is a great deal of overlap between the disciplines of data science and business analytics, the major difference lies in the practical application of data analytics. Data science is a broad field with many subsets, one of those being business analytics.
From financial records to how fast cars travel on the highway, data is everywhere—but not all data is immediately usable. Data science is the practice of taking all the raw data that gets collected and turning it into clear, usable information. Data science investigates quantifiable metrics accumulated by tracking and maintaining extensive amounts of data.
Making collected data usable involves scrubbing, organizing, and analyzing the information. Data science also incorporates statistics, programming, and machine learning to determine the trends present in a dataset. Those trends are then used to help shape decisions of businesses across all sectors through another field known as business analytics.
Business analytics is a branch of data science that interprets collected data to influence business strategy. While data scientists focus on finding solutions to mathematical problems, business analysts focus on finding answers to business questions.
Business analytics uses data to investigate past business performance and create future targets. Serving as intermediaries between the technical and the operational, business analysts typically come from a business background with the desire to shape business practices through the integration of data. These analysts uncover patterns and relationships that guide decision making to create more efficient processes and stay ahead of market trends.
The growing volume of accumulated data worldwide has made data science one of the fastest growing fields across every industry. With a projected growth of 36 percent, data science is the fourth fastest growing career in the U.S. Organizations need data experts to manage and interpret what would otherwise be overwhelming amounts of data and provide actionable recommendations. Data professionals are hired to predict market trends, boost sales conversion rates, reduce costs, and even design new products.
Careers in data science tend to focus on the mathematical, statistical, and technical side of data analysis. These can include:
Data Scientist
Data Analyst
Data Architect
Data Engineer
Machine Learning Engineer
Software Engineer
The integration of metrics with strategy is the trademark of a business analytics career. Professional roles in this field include:
Chief Information Officer (CIO)
Strategy Consultant
Lead Logistics Analyst
Business Intelligence (BI) Analyst
Data Visualization Analyst
Pricing and Revenue Optimization Specialist
While a professional in either field could dip into the other specialization over the course of their career (and many will), there are unique skills that you can master in order to excel on either path.
As technology moves forward and we grow to rely on digital tools, the collection and analysis of data for business strategy is no longer optional. By training to meet the demand for data experts, you can secure your career and change the future of business. Whether you enjoy the detailed aspects of data science or the strategic elements of business analytics, a master’s degree can prepare you for a career in data analytics.
In both data science and business analytics programs, students learn how to organize and analyze empirical data that can be used to inform decision making. The key differences lie in how this analysis is applied and the specific training involved in the process.
Students in a data science master’s program go deeper into the data, concentrating on organizing it, extracting meaning from it, and interpreting it for others. This degree will focus more heavily on the technical aspects of data science, including programming, machine learning, and statistical analysis.
In comparison, students earning a master’s in business analytics will gain a more holistic perspective on the role of data in business. Students are trained in many of the same technical elements as a data science degree while learning how to incorporate their findings into the development of ethical, sustainable business decisions.
Ultimately, the decision to pursue a master’s in business analytics or a data science master’s degree should be determined by your experience, goals, and preferences.
Data science and business analytics won’t be going away anytime soon, and neither will the need for expert data science education. At the UDallas College of Business, we’re proud to offer master’s programs in both of these fields of data science.
Our Master of Science in Business Analytics dives into the technical skills necessary for deriving meaning from big data, as well as the ability to effectively communicate results to key stakeholders. Students learn how to analyze business data through the creation of predictive models in an effort to support ethical and sustainable business decisions.
We are proud to announce our new Master of Science in Data Science and Artificial Intelligence—a program that meets the U.S. Department of Homeland Security's requirements for STEM designation. It is designed for students with a technical degree or related technical work experience who want to better understand the human dimension of data analytics.
Every degree program at UDallas shares a common goal to keep humanity at the forefront of business. Both the M.S. in Business Analytics and M.S. in Data Science programs infuse ethical decision making and sustainable business practices into the field of data science. All of our courses and assignments are rooted in the university’s legacy of critical thinking and ethical leadership that prepares graduates to build their careers on integrity and discipline.
To learn more about potential careers you can pursue in data science, you can explore our free Guide to AI, Data, and Cybersecurity Careers.