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.
Request Info ApplyFlexible 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
From Our Alumni
"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."
Is a business analytics graduate program right for you?
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.
STEM-Designated Master's Program
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.
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.
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
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.
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.
Prerequisite: ISYS 610 for level GR with minimum grade of CThe 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
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.
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.