Analytics and Information Management
Meet your professional potential with Duquesne's Master of Science in Analytics and Information Management (MS-AIM), a business analytics program that equips you to apply data models, explore analytical methods and prepare visualization tools that lead to informed and strategic business decisions.
Through project-based hybrid and online courses, you will learn to use state-of-the-art data analytics tools and establish experience making high-stakes and impactful recommendations in competitive management settings.
Flexible Master's Degree - Choose Your Pathway
Complete your MS in Analytics and Information Management at your own pace with our
flexible degree options. Study full-time or balance your courses with your personal
and professional responsibilities:
- One-year pathway (three semesters): hybrid and online courses
- One-year pathway (three semesters): 100% online courses*
- Two-year pathway (six semesters): hybrid and online courses
- Two-year pathway (six semesters): 100% online courses*
- Certificate-to-MS pathway (three semesters to complete certificate + three additional semesters to earn an MS): hybrid and online courses.
*Most of the analytics and information management degree can be completed online with asynchronous courses, but the capstone class has several synchronous virtual meeting requirements.
Learn More About Duquesne's MS-AIM Degree
In the flexible Master of Science in Analytics and Information Management program,
you will establish business expertise in data analytics and information management,
develop dynamic techniques such as storytelling to share and implement your ideas
and expand your understanding of data manipulation, data modeling, querying, machine
learning and visualizations.
To learn more about Duquesne's MS in Analytics and Information management, request more info and attend an information session.
Program Information
Through project-based hybrid and online courses, you will learn to use state-of-the-art data analytics tools and establish experience making high-stakes and impactful recommendations in competitive management settings.
More in this Program
"The program prepared me for the overall activities needed to be successful in
a data analytics position. It not only gave me tools and techniques to perform the
data analytics project but also showed me how it should be effectively communicated."
Our AACSB International-accredited MS in Analytics and Information Management program
seeks students who are invested in learning new and emerging technologies, approaching
new skills with a "growth mindset" and collaborating with peers, faculty and other
experts in the data management field. Once you graduate and take your expertise into the world, we remain committed to your
success. The business analytics program at Duquesne University connects you with a
powerful network of more than 93,000 alumni across the globe, and as a student and
a graduate, the Center for Career Development will support your professional endeavors
with lifelong career management services.
Our STEM-designated program sets you apart from other MS degree holders.
Duquesne University's rigorous analytics and information management degree is designed
around interdisciplinary skills in technology and modeling, strategic approaches to
complex business challenges and competitive business acumen for navigating a rapidly
expanding global job market.
Specialize your degree with the courses that match your career aspirations. Use Duquesne's
opportunities for credit sharing between programs to pursue a joint degree alongside your MBA, such as a JD, PharmD or MA in Communication, to obtain two graduate
degrees at once. Within the Professional MBA program, you can expand your career-specific skills with
certificates in Analytics and Information Management, Finance, Supply Chain Management, or the hybrid Certificate in Entrepreneurship.From Our Alumni
Is a business analytics graduate program right for you?
STEM-Designated Master's Program
MS-AIM Courses
Statistical and technical understanding are essential for the AIM professional. This
course focuses on creating a solid foundation of technical skills, which will be applied
in downstream courses. Topics will include programming concepts and logic, descriptive,
predictive and prescriptive statistics, and data storage techniques. Prerequisites:
None Hybrid Course, Online. Offered fall only.
Within the context of data analytics, this course teaches students to manage information
as a strategic asset with the potential to create significant business value. Students
will be exposed to various approaches to managing the capture, retention and disposition
of information. Special emphasis will be placed on the legal/regulatory, ethical,
risk management and cybersecurity requirements of managing information. Topics include
the role of information systems in an organization, information systems governance
(which is designed to ensure that IT investments create organizational value), data
governance (which seeks to ensure that organizational data meet the standards for
quality data), and strategies for identifying measurable sources of ROI. Prerequisites:
None Online. Offered fall and summer.
Within the context of data analytics, this course teaches students to manage information
as a strategic asset with the potential to create significant business value. Students
will be exposed to various approaches to managing the capture, retention and disposition
of information. Special emphasis will be placed on the legal/regulatory, ethical,
risk management and cybersecurity requirements of managing information. Topics include
the role of information systems in an organization, information systems governance
(which is designed to ensure that IT investments create organizational value), data
governance (which seeks to ensure that organizational data meet the standards for
quality data), and strategies for identifying measurable sources of ROI. Prerequisites:
None Hybrid Course, Online. Offered fall only.
Increasingly, organizational decision-making relies on data available from a diverse
collection of sources. This course covers the objectives, methods and skills for sourcing
data from both internal and external data sources. Students will be exposed to numerous
data sourcing techniques and methods including ingesting data from common file formats,
web APIs (application programming interfaces), and web scraping. Students will also
learn a variety of methods for examining and enhancing the quality of acquired data.
Pre-requisite: ISYS 610 for level GR with minimum grade of C (may be taken concurrently). Hybrid Course, Online. Offered fall only.
Artificial intelligence (AI) is the science of getting computers to learn and solve
problems autonomously without being explicitly programmed (machine learning). In the
past decade, through machine learning, AI has given us self-driving cars, practical
speech recognition, effective web search, and a vastly improved understanding of the
human genome. Companies are increasingly applying AI technologies and techniques to
uncover new business insights and assist managers with making better informed and
timely decisions. This course will cover concepts and algorithms in artificial intelligence
with an emphasis on machine learning. Students will learn about the most fundamental
machine learning techniques, gain practice implementing them and applying them to
new problems. Prerequisite: ISYS 610 for level GR with minimum grade of C. Hybrid Course, Online. Offered spring only.
Organizations have more opportunities than ever before to collect, organize, and store
internally and externally generated data. Such data are used to support organizational
operations, managerial decision-making, and strategic planning. This course will examine
multiple types of sources of data, including how it is collected and stored in relational
and non-relational databases. The focus is on understanding the structure of the data
and designing structures appropriate for various organizational needs. Lecture, Online, Hybrid. Offered spring only.
"E-commerce and social media have experienced rapid growth during the past decade.
Billions of users have been generating and sharing a variety of social content including
text, images, videos, and related metadata. Social media can be viewed as an indicator
reflecting different aspects of the society, and organizations can combine this with
their existing data to support organizational decision-making. In this course, students
will learn how to analyze behavioral data and apply the analyses to answer business
questions. Advanced regression techniques, network concepts, and social theories will
be covered throughout the course. Prerequisite: ISYS 610 for level GR with minimum
grade of C. " Hybrid Course, Online. Offered spring only.
Two foundational attributes of an outstanding data analyst are: 1) a fundamental ability
to ask insightful business questions using a purposeful, scientific approach, and
2) to be able to tell a ‘story’ regarding how the results of the analytical process
can be turned into operational assets for different stakeholders. Industry leaders
find that being able to build and tell a story using the data are becoming even more
critical than the data extraction skills alone. As such, a focus of this course is
building Socratic questioning and storytelling abilities within the analytics ecosystem.
Other course topics will include project management methodologies, decision-making
models, persuasive presentation techniques, and business process documentation. Prerequisites:
None. Hybrid Course, Online. Offered spring only.
The 21st century has been called by many ‘The Century of Data.’ The explosion of social
media and the digitization of many aspects of social and economic activity have resulted
in the creation of large amounts of rich data in a variety of formats. By applying
advanced analytical techniques to these data, organizations hope to uncover hidden
insights that will yield competitive advantages. This course will introduce strategies
and methods for developing meaningful business intelligence to assist managers in
making decisions in complex environments. The focus will be on using data analysis
to make managerial recommendations as opposed to collecting and managing the data
itself. The key objective of this course is to equip students with knowledge about
how organizations are applying analytical techniques in various business situations,
as well as the associated technical, conceptual and ethical challenges associated
with the application of such techniques. Prerequisite: ISYS 610 for level GR with
minimum grade of C. Hybrid Course, Online. Offered summer only.
"In this course, student teams work with a real company to develop a data analytics-based
recommendation for advancing the business. The project is the program’s capstone experience
designed to provide students the opportunity to utilize the methods, skills and techniques
acquired throughout the program to solve a real-world business challenge. In doing
so, students will experience what it is like to make high-stakes and impactful recommendations
to top management under time-pressure and with high expectations for quality and analysis.
Prerequisites: ISYS 612 with minimum grade of C and ISYS 613 with minimum grade of
C and ISYS 620 with minimum grade of C and ISYS 621 with minimum grade of C and ISYS
622 with minimum grade of C and ISYS 623 with minimum grade of C. " Hybrid Course, Online. Offered summer only.