In a global, digital world, all businesses, products, markets, and economies face
common pressures — make smart decision making faster, make it easier to measure success,
and make success more routine. The B.S. in Business Analytics brings together the
broad application of math and statistics, the intelligent design/computing of data
science, and the business savvy of operations research and management to support success.
As a student in the B.S. in Business Analytics program, you will gain extensive skills
in statistical analysis, data visualization and modeling (descriptive, predictive
and prescriptive). That strong analytical and technical background is balanced by insights into how these
models can be applied across functional business areas.
What Gets Measured, Gets Managed
You will gain exposure to broad business areas (finance and strategic management/marketing),
with a special emphasis on supply chain and operations. Global environment, political,
and social change all make the ability to translate data into insights and smarter
decision making vital for global supply chain and operations.
Concentrations in Business Analytics
Health Systems Engineering
The Health Systems Engineering (HSE) concentration supplements traditional degree
programs in Computer Science, Data Science, and Business Analytics with application
examples based on the challenging problems in the healthcare industry. The concentration
is grounded in the fundamentals of systems engineering and analytics, and focuses
on process improvement, health informatics, health care systems modeling, and healthcare
Systems EngineeringHealthcare ArchitectControl Systems Engineer
Intelligent Mobility uses data and technology to connect people, places, and
goods across all transportation modes. Growth in intelligent mobility will transform
the way people travel, interact with their environment, and connect goods and services.
Connected and Autonomous TransportNew Mobility ServicesOpen Data Platforms for Transport
Logistics and Supply Chain Management
Logistics and Supply Chain Management is the coordination of all logistical functions
in an enterprise including acquisition, handling, the internal allocation of resources,
delivery, and output. Students develop knowledge of the business and technical aspects
of managing large-scale delivery operations. The expert in Logistics/Supply Chain
Management optimizes these complex networks to ensure efficiency and satisfaction.
Strategic SourcingReverse Logistics Global Supply Chain Mapping
Quantitative Economics and Econometrics
Quantitative Economics and Econometrics use mathematical and statistical methods
to develop techniques for measuring a range of systems, including financial, government,
social, legal, medical, and so on. Students with a quantitative economics and econometrics
background learn to assess and measure trends to understand complex phenomena and
to improve long-term positioning.
Market Research AnalyticsEconomic ForecastingCommodities Analytics
Careers in Business Analytics
Business Analytics is much younger as a profession than accounting. The variety of
people, skill sets, job titles, and work environments within Business Analysts is
At the high end of the spectrum, job titles like chief data officer, business intelligence
developer, or business intelligence architect can earn upwards of $200,000. Early
career titles include analytics manager, data-driven decision-maker, functional analyst,
and data systems developer.
According to the U.S. Bureau of Labor Statistics (BLS) data, the employment of management
analysts – including business analysts – is expected to grow 14% from 2014 to 2024,
which is much faster than the average for all occupations.
BLS reports for May 2016 showed that the average annual income for all management
analysts, including business analysts, was $91,910. The middle 50% earned between
$60,950 and $109,170. Salaries for the lowest 10% were around $46,560, while the highest
10% brought in upwards of $149,720.
We live in a world of big data. There are many data sources, but a lot of these data
points or observations don’t necessarily have a label or are annotated. There is a
need for an automated way to identify the correct label or the correct group to which
a particular comment may belong.”