Almost all human activity in the world today is measured and recorded as data. Whether we are listening to music, streaming shows, making a doctor’s appointment or booking a flight – we are generating data. 

Analyzing that data can vastly improve human lives and business performance. So, it’s not surprising that data analytics is now used routinely even in fields not traditionally associated with data – including the arts, music and creative writing. Data analysts are also highly valued and sought after in business, government, health care, education, social welfare, engineering and manufacturing.

Wherever you want to make your mark on the world, a career in data analytics can help you do it.

Program Type


Program Format

On Campus

Why UWM?

With a BS in Data Analytics from UWM, you will train to practice in the field that you’re most passionate about. At UWM, students can tailor their program around six areas to prepare for a data career in that industry: health care, business, social sciences, natural sciences, information science, or geography. With a BS in Data Analytics, you will learn:

  • The  foundations of analysis – this involves calculus, statistics, data mining and computer programming.
  • How to apply data to solving real-world problems.
  • The communications skills critical for presenting data in a professional setting.

A well-trained data analyst serves as a bridge between the data and the users of the data, putting meaning and context to the data while also making sure data is used in an ethical manner.

Portrait of Ainsley, a young woman, standing inside a lab in the Northwestern Mutual Data Science Institute

It’s not just tech companies like Google or Facebook that need skilled employees who can work with data. All industries rely on and use data to make important decisions. Manufacturers need to understand the demand for their product and the shopping habits of their customers. The service sector needs to understand product variations and pricing – for example, airlines that need to schedule different routes and different pricing option for a single flight. Retailers need to understand traffic patterns of in-store shoppers to site new locations. Consulting firms need to crunch data related to the behavior of voters, future college students, and consumers of news so they can best advise their clients. And tech companies need to understand the browsing styles of online users.

Why should you consider a Bachelor of Science in Data Analytics (BSDA)?

With every field turning to data to improve decision-making and performance, Data Analytics is one of the fastest growing professions today but there aren’t enough trained data analysts to fill that need. A degree in Data Analytics that trains you to analyze data can therefore give help you in finding jobs with attractive salaries. 

A report from the employment outlook firm Burning Glass produced jointly with IBM and the Business Higher Education Forum identified several job categories in the data science and analytics field, including data driven decision makers (“leverage data to inform strategic and operational decisions”) and functional analysts (“utilize data and analytical models to inform specific functions and business decisions”).  They estimated a national demand of 1.8 million job postings nationwide for 2020, with a 5-year growth rate of approximately 15%. Importantly, the report also states: “39% of Data Scientists and Advanced Analysts require a Master’s or Ph.D. These degrees take additional years of schooling to complete, so it will take a significant time investment to train a larger pool of workers. Therefore, because these roles are already undersupplied and projected to grow rapidly, the skills shortage is in danger of worsening.”

The Bureau of Labor Statistics also projects that Computer and Information Research Scientists category of jobs will grow 15% over the 2019-2019 period and describes this as: “…much faster than average for all occupations.1 Job prospects are expected to be excellent” and states that the “median annual wage for computer and information research scientists was $126,830 in May 2020.” BLS also classifies this as a category in which most jobs require a Master’s degree.

Additional evidence of demand is also seen in investments made by employers like Northwestern Mutual that have invested significant resources of $15 million in the establishment of the Northwestern Mutual Data Science Institute to support the launch and growth of undergraduate and graduate programs related to data including data science and data analytics.

1 Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, Computer and Information Research Scientists, at (visited January 04, 2022)

Data Analytics or Data Science?

Data analysts and data scientists fill complementary positions in a company. A data scientist has more training in math and computer science and their duties are more related to the computer programming required to build a good database and extract the right data. The scientist then collaborates with an analyst to understand what data is needed for the problem at-hand and what type of data needs to be generated so that they can write their programming code accordingly. Data scientists are also the people who usually create the algorithms needed to analyze data. If you are more interested in computer programming and algorithms, you may wish to explore UWM’s bachelor’s degree in data science.

Overview of the Program

The B.S. in Data Analytics degree consists of 120 credits composed of the following areas: (a) 33 credits of required UW-Milwaukee General Education Requirements, (b) 16 credits of foundations, (c) 33 credits of core courses, (d) 24 credits of Analytics Specialization, and (e) 14 credits of general electives. Students are required to complete a capstone requirement which may be met through an internship, practicum, project, or a thesis in their discipline of interest. The program will be overseen by a faculty oversight committee (FOC) led by a program director. Faculty from participating schools/colleges will make up the oversight committee. 

Student Learning Outcomes and Program Objectives

The core objective of the B.S. in Data Analytics is to prepare students for careers in data analytics in a variety of disciplines and employment settings. The program is designed to allow students to progress through key areas involving distinct learning outcomes. Specifically, graduates of the program will be able to:

  1. Demonstrate a strong understanding of the foundations of data analytics including linear algebra, calculus, statistics, and computer programming.
  2. Acquire knowledge and concepts that represent the fundamentals of data analytics, including programming languages, databases, analytics, big data, data mining and visualization, statistics, communication, and ethics.
  3. Apply data analytics concepts inter-disciplinarily to real-world problems in a variety of fields and settings.
  4. Effectively communicate with users and management during problem formulation, analysis, and investigation, and while presenting the results of the analysis.
  5. Appreciate and abide by ethical uses of data and insights from the analysis.

The core knowledge in these key areas will be reinforced through a capstone course, either through an internship, fieldwork, or a thesis. Furthermore, a unique feature of this degree, students will have the opportunity to pursue analytics electives related to their primary discipline of interest via courses offered in a variety of disciplines including business, biological sciences, computer science, geography, sociology, among others. Finally, students will round out their degree through general electives, which can extend their area of focus, supplement it with electives from complementary areas including nursing, health sciences, and public health, or apply the credits towards a complementary discipline-specific certificate. Additionally, the general education outcomes which are based on the UW System Shared Learning Goals will apply to all students in the program.

Program Requirements and Curriculum

For admission to the B.S. in Data Analytics program, students must meet the general requirements of admission to UW-Milwaukee, including high school graduation with 4 units in English, 3 units in Mathematics, 3 units in Natural Science, 3 units in Social Science, and 4 units in academic electives. Performance on the ACT/SAT may also be considered if desired by the applicant, as is an application essay.

The Table below illustrates the curriculum for the proposed program. The program requirements are comprised of 120 credits, of which there are 16 credits of foundations, 33 credits of core courses, 24 credits of analytics specialization courses, and 14 credits of general electives, and UW-Milwaukee general education requirements.

General education and breadth courses (33 credits)

Oral and Written Communication Part A3
Oral and Written Communication Part B: ENGLISH 205 Business Writing3
Quantitative Literacy Part A Algebra Requirement3
Quantitative Literacy Part B Calculus Requirement: MATH 208
or one of 211 or 213, 221, 231
Natural Sciences including one lab or field experience6
Social Sciences6
Foreign Language 

Foundations (16 credits)

MATH 240 Matrices and Applications3
MATH 212 Survey in Calculus and Analytic Geometry II4
BUS ADM 210 Statistical Modeling in Business Analytics or
BUS ADM 211 Business Scholars: Statistical Modeling in Business Analytics or
Econ 210 Economic Statistics or MTHSTAT 215 Elementary Statistical Analysis
Computer Literacy 1
BUS ADM 230 Introduction to Information Technology Management,
HS 224 Computational Tools for Healthcare Professionals,
COMPSCI 150 Survey of Computer Science
Computer Literacy 2
COMPSCI 202 Introductory Programming Using Python,
240 Introduction to Engineering Programming,
250 Introductory Computer Programming, or
INFO ST 350 Introduction to Application Development
a computer literacy 1 and 2 can be satisfied by COMPSCI 250 and 251

Core courses (33 credits)

Programming Languages
(2 of the following 10 courses – 6 credits)

BUS ADM 335 Introduction to Business Application Development3
BUS ADM 432 Object-Oriented Systems Development3
INFO ST 350 Introduction to Application Development*3
INFO ST 440 Web Application Development3
BIO SCI 502 Introduction to Programming and Modeling in Ecology and Evolution3
COMPSCI 351 Data Structures and Algorithms3
MTHSTAT 216 Introduction to Statistical Computing and Data Science or
MTHSTAT  566 Computational Statistics  
GOEG 325 Introduction to Data Science with R, Python, and GIS 3
GOEG 215 Introduction to Geographic Information Science3
GOEG 525 Geographic Information Science 3
*INFO ST 350 cannot be used in this category if it was used to satisfy the Computer Literacy 2’ requirement 

(1 of the following 4 courses – 3 credits)

BUS ADM 434 Data Base Management Systems3
INFO ST 410 Database Information Retrieval Systems3
HCA 537 Health Information Technology and Management3
Comp Sci 557 Introduction to Database Systems3

Analytics and Big Data/Data Mining
(2 of the following 8 courses – 6 credits)

BUS ADM 336 Enterprise Systems and Data Analytics3
BUS ADM 536 Business Intelligence3
INFO ST 582 Introduction to Data Science3
INFO ST 687 Data Analysis for Data Science3
AtmSci 600 Data Analytics3
COMPSCI 411 Machine Learning and Applications    3
COMPSCI 422 Introduction to Artificial Intelligence3
COMPSCI 425 Introduction to Data Mining3
Econ 411 Economic Forecasting Methods3
INFO ST 691 Special Topics – Computer Forensics*3
*Other topics offered in a specific offering of this course must be approved for the degree by the Prog. Dir.

(1 of the following 3 courses – 3 credits)

BUS ADM 438 Information Technology Management Topics: Social Network Analytics3
INFO ST 370 Data Analysis and Visualization for the Information Professional3
GOEG 405 Cartography3

(2 of the following 5 courses – 6 credits)

MTHSTAT 361 Introduction to Mathematical Statistics I3
MTHSTAT 362 Introduction to Mathematical Statistics II3
ATM SCI 500 Statistical Methods in Atmospheric Sciences3
ECON 413 Statistics for Economists3
ECON 513 Introduction to Econometrics3


ENGLISH 310 Writing, Speaking, and Technoscience in the 21st Century3

Ethics (1 of the following 6 courses – 3 credits)

BUS ADM 530 Introduction to eBusiness3
HS 311 Law and Ethics for Healthcare Professionals3
PHILOS 237 Technology, Values, and Society3
COMPSCI 395 Social, Professional, and Ethical Issues3
SOCIOL 327 Data, Technology, and Society3
INFO ST 661 Information Ethics3

Capstone / Fieldwork / Thesis
(1 of the following 21 courses – 3 credits)

BUS ADM 389 Real Estate Internship3
BUS ADM 394 Human Resources Management Internship3
BUS ADM 396 Finance Internship3
BUS ADM 397 Marketing Internship        3
BUS ADM 398 Supply Chain & Operations Management Internship3
BUS ADM 400 Accounting Professional Internship3
BUS ADM 439 Information Technology Management Professional Internship3
BUS ADM 459 Finance Professional Internship3
BUS ADM 469 Marketing Professional Internship3
BUS ADM 479 Supply Chain & Operations Management Professional Internship3
BUS ADM 494 International Business Internship3
BUS ADM 534 Information Technology Practicum3
BUS ADM 600 Management Analysis3
Econ 489: Internship in Economics, Upper Division3
INFO ST 408 Nonprofit Information Technology3
INFO ST 490 Senior Capstone3
INFO ST 495 Information Internship3
Comp Sci 595 Capstone Project3
MTHSTAT 489 Internship in Mathematical Statistics, Upper Division3
MATH 599 Capstone3
GOEG 600 Perspectives on Geography3
GOEG 698 GIS/Cartography Internship3

Electives in an area of specialization
(choose 24 credits in an area)


BUS ADM 536 Business Intelligence3
BUS ADM 532 Web Development for Open Business Systems3
BUS ADM 533 Introduction to Connected Systems for Business3
BUS ADM 537 Enterprise Systems Concepts and Issues3
BUS ADM 539 Web Application Server Development3
BUS ADM 540 ERP Certification3
BUS ADM 370 Introduction to Supply Chain Management3
BUS ADM 478 Supply Chain Analytics3
BUS ADM 571 Quality and Six Sigma Tools3
BUS ADM 436 Systems Analysis and Design3
BUS ADM 360 Principles of Marketing3
BUS ADM 462 Marketing Research 3
BUS ADM 350 Principles of Finance and3
BUS ADM 450 Intermediate Finance3
BUS ADM 451 Investment Finance3
BUS ADM 457 Financial Modeling3
BUS ADM 458 Venture Finance3
Recommend: BUS ADM 300 Career and Professional Development3

Information Science and Technology

INFO ST 240 Web Design I3
INFO ST 350 Introduction to Application Development3
INFO ST 315 Knowledge Organization for Information Science and Technology3
INFO ST 340 Introduction to Systems Analysis3
INFO ST 320 Web Design II3
INFO ST 325 Information Security I3
INFO ST 375 Multimedia Web Design3
INFO ST 383 Native Mobile Applications3
INFO ST 430 Multimedia Application Development3
INFO ST 465 Legal Aspects of Information Products and Services3
INFO ST 583 Survey of Information Security3
INFO ST 584 Survey of Web and Mobile Content Development3
INFO ST 695 Ethical Hacking I3
INFO ST 491* Advanced Topics in Information Science & Technology;3
INFO ST 691* Special Topics in Information Science3
*Topics must be approved by the Prog. Dir. A topic cannot be used here if it was applied to a prior degree requirement category. 


This specialization will require 3-6 credits from a different specialization as approved by the Program Director.

HCA 444 Introduction to Text Retrieval and Its Applications in Biomedicine3
HCA 307 Epidemiology for the Health Sciences3
HCA 541 Healthcare Information Systems Analysis and Design3
HCA 542 Healthcare Database Design and Management3
PH 355 Public Health Research Methods I3
PH 410 True Lies: Consuming and Communicating Quantitative Information3
PH 455 Public Health Research Methods II3
Recommend: HS 222 Language of Medicine
or BMS 205  Introduction to Diagnostic Medicine 
or NURS 352 Health and Illness Concepts 1: Introduction 

Natural Sciences

BIO SCI 469 Genomic Data Analysis3
FRSHWTR 640 Sequence Analysis3
FRSHWTR 504 Quantitative Freshwater Analysis3
FRSHWTR 514 Analytical Techniques in Freshwater Sciences3
MTHSTAT  563 Regression Analysis3
MTHSTAT  564 Time Series Analysis3
MTHSTAT  568 Multivariate Statistical Analysis3
MATH 571 Introduction to Probability Models3
ACTSCI 391 Investment Mathematics I3
ACTSCI 591 Investment Mathematics II3
ACTSCI 593 Actuarial Models I3
ACTSCI 594 Actuarial Models II3
ACTSCI 596 Actuarial Statistics I3
ACTSCI 597 Actuarial Statistics II3

Social Sciences

Choose at most one of the following methods courses:

CRM JST 662 Methods of Social Welfare Research        3
POL SCI203 Introduction to Political Science Research3
PSYCH 325 Research Methods in Psychology       3
AFRIC 301 Research Methods in African & African Diaspora Studies3
SOCIOL 361 Research Methods in Sociology3

Choose at most one of the following multiple regression courses:

ECON 310 Research Methods for Economics       3
PSYCH 610 Experimental Design3
SOCIOL 461 Social Data Analysis Using Regression3

Take courses from the list below to complete 24 credits:

CRM JST 510 Introduction to Crime Analysis3
CRM JST 520 Analysis Oriented Technology: Spatial Data Analysis;
Crime Mapping; ArcGIS 
GOEG 215 Introduction to Geographic Information Science3
GOEG 525 Geographic Information Science3
GOEG 547 Spatial Analysis3
POL SCI390 Political Data Analysis3
POL SCI392 Survey Research3
PSYCH 510 Advanced Psychological Statistics        3
SOCIOL 352 Social Networks3


GEOG 403 Remote Sensing: Environmental and Land Use Analysis   3
GEOG 437 Qualitative Methods in Geography qualitative data is data3
GEOG 547 Spatial Analysis3
GEOG 515 Watershed Analysis and Modeling3
GEOG 625 Intermediate Geographic Information Science 3
GEOG 647 ArcGIS Programming with Python3
URBPLAN 591 Introduction to Urban Geographic Information Systems GIS in Planning3
CRM JST 520 Analysis Oriented Technology: Spatial Data Analysis3

Are you interested in learning more about the Data Analytics program? You can contact the program advisor at

During your time at UWM, you may have multiple members of your success team, including advisors, peer mentors, and success coaches. Your college advisor will help you:

  • Define your academic and life goals
  • Create an educational plan that is consistent with those goals;
  • Understand curriculum, major and degree requirements for graduation, as well as university policies and procedures; and
  • Find campus and community resources and refer you to those resources as appropriate.

The scholarship process for all students and all scholarships (major specific ones and all general scholarships) begins with UWM’s Panther Scholarship Portal.

The first time you log in, you will need to create your general application; this will stay on file for four years but you should update it regularly and must, at a minimum, sign it once per year to re-activate it. You will also need to upload a copy of your transcript twice a year. Log into the Panther Portal twice a year to update your application and upload a newer transcript – we recommend doing this in November/December and in February/March every year.

You may see scholarships on your Panther Scholarship Portal dashboard that you can “Apply To.” These are scholarships which require additional information beyond the general application and transcript. If you do not see “Apply To” you are still being considered as long as your general application and transcript are up-to-date.