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The real difference between business analytics and data science

Thursday, August 01, 2019 | 12:00 AM

As we’re now firmly into the 21st century, some job titles are trending more than others. You’ll certainly find fewer (if any) elevator operators, video store owners, and encyclopedia salesmen. To adapt to today’s conditions as well as prepare for the future, new jobs have surfaced to meet the demands of our modern, technology-driven society. Two fields of study - business analytics and data science - can help you gain the skills you need to be competitive in today’s workforce and to take on impactful and challenging roles.

As a business analyst or data scientist, you will learn how to apply your knowledge to solve important problems in private industry, government, or non-profit organizations. Although these job titles are highly in-demand and seem similar, business analytics and data science are distinct fields that require unique skill sets. Here are the main similarities and differences between the two.

Similarities Between Business Analytics and Data Science

Both business analytics and data science leverage data to improve organizations by gathering and managing data, modeling and forecasting, and making valuable insights that influence business decisions.

A master’s degree is often required to advance your career in these fields, open opportunities for upper-level positions, and increase your earning potential. Being able to program in R, Phython, and SAS is critical to analyze data in both disciplines.

Business Analytics Uses Company Data to Make Immediate Business Decisions

To solve well-defined business problems, business analysts use advanced statistics that analyze company data, such as cost and profit, to understand past performance and predict future performance. Their findings help a business make practical changes and improve efficiency and organization. Business analysts are vital to a company’s day-to-day decision-making.

Analysts come from a variety of backgrounds, including management, business, finance, IT, or computer science, before earning a graduate degree in business analytics. A master’s program in business analytics is flexible because it empowers people from any background to learn statistical analysis, predictive analytics, data visualization, and effective communication to provide clear and actionable recommendations to business leaders.

Business analytics does not involve extensive coding or math and is a great career fit for those who enjoy solving complex problems and offering practical, data-driven conclusions.

Data Science Provides Insights for Future Business Growth and Development

Combining statistics and modeling with computer science, data scientists use algorithms and big data about customers or product users to answer broad questions. They find patterns and connections between factors like geography, buying behavior, or seasons. Their insights are used to help companies make informed decisions about future business development.

Data scientists have more specialized technical skills than do business analysts. They code and build algorithms and then run statistical analyses. Using machine learning and artificial intelligence is increasingly common in data science. A master’s degree is sometimes needed for this field, which appeals to people who have a strong background in math or computer science.

Business analytics and data science are distinct, but both offer lucrative career paths and unlimited potential.

Learn more about the 100% online Master of Science in Business Analytics from the University of Texas Rio Grande Valley.


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