Arizona State University - W.P. Carey School of Business
Arizona State University offers an online master of science (MS) in business analytics. This fully online program teaches students how to analyze and extract information from data.
The program is taught by the same faculty as the full-time on-campus program. It is ideal for students who have two or more years of professional experience.
The major admission requirements for the program include a bachelor's or master's degree from a regionally accredited institution, a minimum cumulative grade point average of 3.0, a completed graduate admission application, official transcripts, GMAT or GRE scores, one letter of recommendation, a current resume, and proof of English proficiency.
Made up of 30 credit-hours, the program helps students deepen their analytical and quantitative skills. The curriculum includes courses such as an introduction to enterprise analytics, data mining, business analytics strategy, data-driven quality management, analytical decision modeling, and an introduction to applied analytics.
Students in this distance-based program are able to learn at their convenience and develop their skills in this growing field. On successful completion of the program, graduates can take up roles as data managers, data analysts, IT specialists, network security analysts, IT managers, or marketing managers, among others.
Carnegie Mellon University - Tepper School of Business
The Tepper School of Business at Carnegie Mellon University offers an online master of science in business analytics program. This instructor-led program is predominantly-online including three optional on-campus visits. The program’s on-campus components include a “basecamp,” a business analytics immersion, and a capstone project. The program faculty includes skilled members who are experts in business analytics. The program is ideal for students with a technical background who wish to advance their technical skills and take up senior analyst positions.
Applicants to the program must have a four-year undergraduate degree or equivalent from an accredited institution, and submit a completed online application, unofficial transcripts of all academic work, an official GMAT or GRE score report, a current resume, two professional letters of recommendation, essays, and TOEFL/IELTS scores for students with English as a second language.
The curriculum provides students with knowledge and practical skills in areas such as methodology, software engineering, and business communication. Some of the courses in the curriculum are an introduction to probability and statistics, business fundamentals for analytics professionals, statistical foundations of business analytics, modern data management, data exploration and visualization, business value through integrative analytics, and managing teams and organizations.
The program teaches students how to identify the challenges of applying data analytics in a business environment, communicate effectively, apply computer software for implementing analytical techniques, and make appropriate judgements regarding manipulating, analyzing, and managing large data sets.
Graduates of the program can pursue roles in operations and supply chain management, business intelligence, analytical marketing, finance, and consulting.
Maryville University offers an online master’s in business data analytics program. This 100 percent online program requires no campus visits. The program teaches students how to combine analytical tools with operational data for presenting complex and competitive information. The faculty for the program includes renowned professionals in the field of business data analytics.
In order to get accepted into the program, applicants must have a bachelor’s degree from a regionally accredited institution, a cumulative grade point average of at least 3.0, and a personal letter explaining qualifications for graduate work. Also, international applicants must demonstrate English proficiency. GRE or GMAT scores are not required for admission.
Consisting of 30 credit-hours, the curriculum is designed to provide students with in-depth knowledge and skills in several aspects of data analytics. Some of the topics students delve into include advanced topics in data analytics, forecasting and predictive modeling, data warehousing, data analytics, database principles, data mining, and data visualization.
Students gain essential skills such as combining analytical tools with operational data, presenting competitive and complex information, and delivering high-quality, timely analytics. The program opens up several opportunities for graduates. They can take up roles as management analysts, management consultants, market research analysts, or operations research analysts, among other opportunities.
Boston University offers an online master of science in applied business analytics degree. This program can be completed online as well as on campus. The program provides students with opportunities and hands-on experience, and is taught by expert faculty members with real-world experience.
Admission requirements for the program include a bachelor’s degree from a regionally accredited institution, a completed application for graduate admission, three letters of recommendation, a personal statement, a current resume, transcript from each college and graduate school attended, and proof of English proficiency for all international applicants. Standardized test scores are not required for admission.
The program comprises of 40 credit-hours. Courses include business analytics foundations, operations management, financial concepts, quantitative and qualitative decision-making, enterprise risk analytics, marketing analytics, and web analytics for business.
Students learn how to choose analytical methods for monitoring and identifying performance issues, analyze data-driven business processes, and propose solutions. At the end of the program, graduates can pursue opportunities as management analysts, mathematicians and statisticians, financial analysts, operations research analysts, and market research analysts.
University of Maryland - Robert H. Smith School of Business
The University of Maryland’s Robert H. Smith School of Business offers an online master of science in business analytics degree program. The program provides students with opportunities, helping them develop data-backed business strategies. The faculty for the program provide students with career advice, along with guidance through the coursework.
The major admission requirements for the program include the equivalent of a US bachelor's degree, a strong quantitative background, an online application form, an essay, a resume, official undergraduate and graduate transcripts, GMAT or GRE scores, a letter of recommendation, and TOEFL or IELTS scores for students who do not have a four-year (or advanced) degree from a country where English is the official language.
The program consists of 30 credit-hours and the curriculum helps students develop their analytics expertise across a variety of focus areas, such as modeling, quantitative analysis, predictive analytics, and more. The curriculum explores topics such as data, models and decisions, data mining and predictive analytics, database management systems, decision analytics, social media and web analytics, big data, and artificial intelligence.
Students develop skills in data mining, SQL, quantitative modeling, data management, and more. Also, they learn how to make predictions and decisions using data, becoming well-rounded leaders in analytics. Graduates of the program can pursue roles in consulting, healthcare, banking and insurance, sports management, hospitality, and communications and media.
Saint Mary’s University of Minnesota offers an online master of science in business intelligence and data analytics. The is a fully online program and does not require students to attend Saint Mary’s brick-and-mortar campuses. The faculty for the program includes experts who have extensive professional and academic experience. These faculty members are versed in platforms such as Tableau, Alteryx, and Python.
Applicants to the program must submit proof of an undergraduate degree from a regionally accredited institution (minimum grade point average of 2.75), a written statement, two letters of reference or recommendation, a resume, and English proficiency test scores for students whose native language is not English. GRE scores are not required and GMAT scores are required only if the student has fewer than five years of work experience.
Comprising 36 credit-hours, the program is designed to make students knowledgeable and skillful in programming languages. They can choose between R and Python, or even take both.
The curriculum explores topics such as managerial economics, business statistics, ethics in data analytics, business modelling, business analytics, data analysis, storytelling, data visualization, data mining for decision-making, and communications and content strategies.
Graduates of the program are well-equipped to work as management analysts, senior business intelligence analysts, computer and information research scientists, data scientists, and financial analysts.
Bellevue University offers an online master of science in business analytics. This fully online program is ideal for students interested in information systems and business disciplines such as project management, business administration, computer information systems, and management information systems. The program provides students with opportunities such as performing data-mining with the help of real world examples.
In order to get accepted, applicants must have a bachelor’s or master’s degree from a regionally accredited college or university (or a U.S. equivalent degree from a nationally or internationally accredited college or university), a grade point average of 2.5 or better, letters of recommendation, essays, and TOEFL test scores for international students.
Consisting of 36 credit-hours, the program helps students enhance their career by providing them with the skills needed for analyzing, designing, and implementing business analytics projects. Some of the course topics include business performance management, business analysis for decision-making, business system programming, advanced business analytics, SAS programming for business, enterprise data, and information management.
Through the program, students learn how to apply business analytics principles to real-world situations; design systems for supporting business analytics; and implement statistical, business analytics, and quantitative tools.
Graduates of the program can pursue roles such as lead business analyst, business analytics project manager, data scientist and business analytics consultant. Additionally, they can also pursue certifications in analytics.
University of North Carolina, Wilmington - Cameron School of Business
The University of North Carolina, Wilmington Cameron School of Business offers an online master of science in business analytics. This 100 percent online program is designed for working professionals providing maximum flexibility.
Admission requirements for the program include a bachelor's degree from an accredited college or university, a minimum grade point average of 3.0, two letters of recommendation, a current resume, and official transcripts from all colleges or universities attended.
Made up of 30 credit-hours, the program provides students with a strong foundation in application and programming development. They learn how to create data graphics and generate statistical reports. Some of the topics students will explore include descriptive analytics, prescriptive analytics, predictive analytics, case studies in business analytics, applications of business analytics, programming for analytics and database for analytics.
The program teaches students how to perform analytics on business projects; collect and transform data into usable formats; use analytics modeling techniques for simulation, decision making, and optimization; and develop a strong foundation in programming.
On successful completion of the program, graduates can pursue roles in healthcare, marketing, supply chains, cybersecurity, transportation, and more.
Stephen Hill, PhD Cameron School of Business
Dr. Stephen Hill is an associate professor of business analytics at the University of North Carolina, Wilmington. He teaches courses in business analytics, operations management, and supply chain management. Prior to joining the University of North Carolina at Wilmington, he worked at Weber State University.
Dr. Hill’s research efforts are focused on the application of analytics techniques in a variety of areas such as sports, healthcare, and supply chains. His research has been published in top journals such as the Journal of Statistics Education, the Information Systems Education Journal, and the International Journal of Information and Operations Management Education. He completed his PhD in operations management, his MS in operations management, his MS in civil engineering, and his BS in civil engineering—all at the University of Alabama.
Uday Kulkarni, PhD, MBA W.P. Carey School of Business
Dr. Uday Kulkarni is an associate professor of information systems at the W.P. Carey School of Business at Arizona State University. Some of the classes he teaches include business intelligence, decision-making with data analytics, business analytics strategy, and business intelligence strategy.
Dr. Kulkarni’s research efforts are centered around brand engagement, knowledge management, business intelligence capability, and decision support. His work has appeared in influential journals such as the Journal of the Association for Information Systems, the Journal of Enterprise Information Management, and the Journal of the Operations Research Society. He has won various awards, including the W.P. Carey Outstanding Graduate Teaching Excellence Award and an Outstanding Faculty Award. Dr. Kulkarni holds his PhD from the University of Wisconsin-Milwaukee, his MBA from the Indian Institute of Management, and his BS from the Indian Institute of Technology.
Dokyun Lee, PhD Tepper School of Business
Dr. Dokyun Lee is an assistant professor of business analytics at the Tepper School of Business at Carnegie Mellon University. He teaches courses such as mining unstructured data, data mining, and deep learning for business.
Dr. Lee’s research efforts are focused on the application, development, and impact of machine learning in business, the economics of unstructured data, interpretable machine learning, and unintended consequences of machine learning. He has published his research in prominent journals such as Management Science, the Journal of Marketing Research, and Information Systems Research. He earned his PhD from the Wharton School, University of Pennsylvania, his MS from Yale University, and his BS from Columbia University.
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