Analytics & Information Management
Transform Data into Business Insights — Become an expert in data analytics and information management with Duquesne's Master of Science in Analytics and Information Management (MS-AIM). Expand your understanding of data manipulation and modeling, querying, machine learning, and visualizations. Through project-based hybrid and online courses, you will use state-of-the-art tools and gain experience making high-stakes recommendations that lead to strategic business decisions.
Is a business analytics graduate program right for you?
Our AACSB International-accredited MS-AIM 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.
We remain committed to your success after graduation. Duquesne University connects you with a powerful network of more than 93,000 alumni across the globe. As a student and a graduate, the Center for Career Development will support your professional endeavors with lifelong career services.
STEM-Designated Master's Program
Our STEM-designated program sets you apart from other MS degree holders. This degree
is designed around interdisciplinary skills in technology and modeling, strategic
approaches to complex business challenges, and competitive business acumen for navigating
the rapidly expanding global market.
Flexible Program
Complete the MS-AIM at your own pace with our flexible program options. Study full-time or balance your courses with your personal and professional responsibilities:
1 Year Pathway
- Three (3) semesters
- Hybrid and online courses or 100% online courses*
2 Year Pathway
- Six (6) semesters
- Hybrid and online courses or 100% online courses*
Certificate-to-MS Pathway
- Three (3) semesters to complete certificate and three (3) 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.
Program Information
Become an expert in data analytics and information management by expanding your understanding of data manipulation and modeling, querying, machine learning, and visualizations. Through project-based hybrid and online courses, you will use state-of-the-art tools and gain experience making high-stakes recommendations that lead to strategic business decisions.
More in this Program
The Information Systems and Technology (IST) Mentoring Program connects MS-AIM students with experienced professionals and allows alumni to remain engaged with the School. It is led by Dr. Wenqi Zhou, an Associate Professor
of IST, in collaboration with the Information Systems and Technology Advisory Council (ISTAC). Program Details Modern organizations use database management systems to store their critical business
data. In this course, students learn to answer business questions using various data retrieval,
manipulation and transformation tools. For instance, data retrieval for most data-driven business applications relies on
Structured Query Language (SQL) – the international standard language for data manipulation
and retrieval. To source the data required by analytics projects, students will learn to utilize
SQL along with other data-related concepts and languages. Prerequisites: None In this course, students will learn how to analyze online behavioral data and apply
the analysis results to explain phenomena and user choices occurred at online platforms,
including e-commerce and social media sites. Various analytical techniques will be
introduced, such as statistical comparison, controlled experiment, and linear and
advanced regression models. In parallel, using real-world data, students will also
learn the basic concepts in web analytics, search engines, social networks, etc. Through
hands-on exercises and projects, students will apply these concepts and select appropriate
techniques to answer business questions, summarized by reports and presentations. Big Data is a concept that includes the strategies and technologies to handle vast
datasets that traditional data processing tools cannot manage. On the other hand,
Cloud Computing offers the scalable and flexible infrastructure necessary for executing
these extensive data processes cost-efficiently and effectively. In this course, students
will explore how Cloud Computing can be designed and built for Big Data analytics
by providing the necessary computing resources to analyze large volumes of data. The curriculum is designed to equip participants with practical knowledge and hands-on
experience on leading cloud platforms such as Amazon Web Services (AWS), Google Cloud
Platform (GCP), and Microsoft Azure. Students will learn to adeptly leverage these
platforms' services to store, process, and analyze large datasets with efficiency
and precision.
IST Mentoring Program
Applications open at the beginning of September and students are matched with professionals
based on specific criteria. The program runs during the Academic Year and is structured
as follows:
Program Contact
Dr. Wenqi Zhou
Course Descriptions
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.
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.
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
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.
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
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, ISYS 613, ISYS 620, ISYS 621, ISYS 622, and ISYS 623—all
with a minimum grade of C
From Our Alumni