Management Information Systems

• QST IS 223: Introduction to Information Systems
  Undergraduate Prerequisites: QST SM 131.
  Provides students with an understanding of the important role that information and information technology play in supporting the effective operation and management of business. Elaborates on the themes of "place to space" and the implications for business of the digital enterprise. Focuses on learning IS concepts in the context of application to real business problems.
• QST IS 428: Managing Information Security
  Undergraduate Prerequisites: QST IS 223.
  Combines technical and business approaches to the management of information. It will address technical issues such as cryptography, intrusion detection, and firewalls along with managerial ideas such as overall security policies, managing uncertainty and risk, and organization factors. We will examine different aspects of computer security such as password, virus protection, and managing computer security in dynamic environments. Topics will also include network security and how to secure wireless application and services. These technical details will be placed in a business context. The class will have a practical focus as we examine current "best practices" in area. There will be several guest speakers in the security area. This will be a project-oriented class and students will present their research projects during the last several classes. 4 cr.
• QST IS 465: Managing Data Resources
  Undergraduate Prerequisites: QST IS223; QST BA222 or CAS CS105 or CAS CS108 or CAS CS111 (co-requisite /pre-requisite)
  Required for Management Information Systems concentrators. Provides a practical and theoretical introduction to data management focusing on the use of relational database technology and SQL to manage an organization's data and information. Introduces recent topics such as data warehouses and Web databases. Includes a project to design and implement a relational database to manage an organization's data. 4 cr.
• QST IS 467: Agile Development Methodologies
  Undergraduate Prerequisites: QST IS223; QST BA222 or CAS CS105 or CAS CS108 or CAS CS111 (co-requisite /pre-requisite)
  This course is designed to provide the students with an overview of Agile Development methodologies. The course introduces the various methods currently used in the industry and then focuses on the primary methodologies used today, SCRUM and Kanban. Students will learn the tools of these software development approaches that produce deliverables to end users every two to four weeks. We analyze the value each of these methodologies bring into the development process and the reasoning behind a corporation selecting one method over the other (or a combination of both). In addition, the students will be introduced to CA Project Management software, the leader in the industry for SCRUM. Students will learn to analyze requirements, create backlogs, schedule "stories" to be developed, hold Standup meetings, Reviews and Retrospectives.
• QST IS 469: Designing Information Systems
  Undergraduate Prerequisites: QST IS 223.
  Required for Management Information Systems concentrators. Studies the process of designing and implementing management information systems. Students will learn to analyze organizational information requirements, develop specifications for information systems, manage systems development projects, and understand implementation issues. Key implementation concepts that affect management decisions will be discussed, and reinforced with programming examples. Design support tools will be used to support the design process. Includes a project to design an information system.
• QST IS 474: Platform Strategy & Design
  Undergraduate Prerequisites: QST IS 223.
  Today's most valuable and powerful companies do not offer standalone products or services, but rather platforms which enable transactions between multiple customer groups -- think Alibaba, Airbnb, Amazon, eBay, Facebook, Google, Microsoft, Salesforce, Uber, etc. This course explores the unique strategy challenges and economic foundations of such platform businesses. What makes platforms special relative to regular product businesses? Why are platforms so powerful, yet so hard to build? How should platforms be designed and priced? How much responsibility should platforms take for bad things they enable their participants to do (e.g. fake news and ad scams on Facebook, counterfeits on Alibaba)? When and how can regular products or services be transformed into platforms? How should other businesses deal with the rising power of platforms that they depend on? The course will use a mixture of conceptual frameworks, (light) economic models, and case studies to provide students with a thorough and in-depth understanding of what it takes to build or invest in platforms. Such an understanding is indispensable to anyone seeking a career at technology companies or aspiring to become an entrepreneur or venture capitalist.
• QST IS 479: Innovating with Information Technology
  Undergraduate Prerequisites: QST IS 223.
  Surveys the organizational implementation, uses, and impacts of advanced information technology including decision support systems, management support systems, and expert systems. Includes a group project to design and develop a decision support system.
• QST IS 498: Directed Study: Management Information Systems
  Directed study in Management Information Systems. 2 or 4 cr. Application available on Undergraduate Program website.
• QST IS 711: IT Strategies for a Networked Economy
  Graduate Prerequisites: QST MO712 or MO713, QST AC710 AC711, QST QM716 or QM717
  This case-based course demonstrates the role that information technology plays in shaping business strategy and business models. It provides an overview of the key technologies that are important in today's business environment and introduces organization and management concepts relating to the information technology function. The course also illustrates the relationships between organizational performance and the ability to leverage knowledge assets.
• QST IS 717: Systems Architecture in Management and Applications
  Graduate Prerequisites: MSDT students only
  The objective of this course is to provide an overview of the concept of systems architecture and how it has evolved from a technical notion to an important business issue. The course has several themes: (1) Students develop an appreciation of how a business may leverage architectural design choices for operational and competitive advantage, both at a technical and business level. (2) Students obtain insight into how interface driven systems (those using APIs) enable flexibility and increased innovation. (3) Students are confronted with the difficult aspects of modern systems, such as parallelism and concurrency, and how these technical challenges are managed. An introduction to programming in Python provides a context to help students develop a hands-on understanding of these concepts. Care is taken to not just apply the technical material to management contexts, but also inform business strategy and organization and operations through these architectural principles.
• QST IS 737: Decision Making with Data
  Graduate Prerequisites: QST IS717, IS833, IS834, QM877, or knowledge of Python
  This is an advanced python-based analytics course on data-driven decision-making in business environments. Business analytics professionals need to be able to i) uncover patterns in the data (descriptive analytics); ii) use the data to make predictions about future outcomes (predictive analytics); and iii) leverage this data to make optimal business decisions (prescriptive analytics). This course takes a holistic approach to analytics, touching on aspects of all three descriptive, predictive, and prescriptive pillars. We explore advanced business analytics topics, including data reduction, classification, decision analysis, and optimization. We link data models to strategy relying on statistical programming in Python and introduce novel techniques used in practice. Case studies and projects apply topics to practical business problems. 3 cr.
• QST IS 754: Human Centered Design
  Graduate Prerequisites: MSDT students only
  When constructing digital artifacts, either for internal or external consumption, creating a coherent and well-motivated design is essential. This class will explore the language and key principles of design and how these impact the user experience. We will also cover the essentials of project management, including scoping as a design constraint. Students will be asked to critique existing designs and offer alternatives. Additionally, we will cover the programming topic of object orientation, and study both it and the structures it enables from a design perspective.
• QST IS 756: Digital Project Build
  Graduate Prerequisites: MSDT students only
  The modern economy is driven by dynamic websites: those whose content is created on the fly by programs, not humans. In this class we will learn the technology behind both static and dynamic websites. Students will be exposed to the concepts through lectures and labs, and ultimately by the construction of a complete dynamic website in Python using our custom infrastructure built on Google App Engine.
• QST IS 811: Responsible AI for Business Analytics
  AI and data are powerful tools that require thoughtful and responsible applications. The stakes are high as algorithms can scale to influence millions and even billions of people within a moment of launch and morph businesses and society with the impact that might last generations. Our mission is to understand and anticipate potential pitfalls and misuse of personal data and AI to guard against harm. We will also discuss existing solutions and the lack of solutions. The course is designed to be accessible to everyone and targeted to practitioners whose businesses will use some form of data and algorithms. Examples from Technology, Retail, Marketing, Health Care, Finance, and Society will be discussed.
• QST IS 815: FinTech Revolution: Disruptive Technologies, Blockchain and Future of Finance
  FinTech is the intersection of finance, technology, and regulation. The course aims to help students understand FinTech and recognize the challenges and opportunities the innovations within FinTech pose. Students gain a basic understanding of the foundations and principles that enabled the rise of FinTech and examine cases for a more in-depth analysis of specific innovations such as blockchain and cryptocurrencies. The course advances students' knowledge of FinTech, much needed skill in the industry, and gives students insight into the applications, limitations, and risks of technological innovations in finance.
• QST IS 823: Analytics for Managers
  This non-programming-based analytics course examines how the abundance of data has transformed decision making in organizations and the strategic implications of this transformation. We explore how data are being used, ranging from the core principles of properly identifying data sources to the actual analytical methods being used to solve a wide range of business problems. Students will have some hands-on work with advanced Excel, Tableau, and two database applications, Microsoft Access and Neo4j (Neo4j is used to compare and contrast SQL and NoSQL databases in an analytics context). At the end of this course, students will have gained a big-picture perspective on business analytics as well as hands-on experience with commonly-used business analytics software.
• QST IS 827: Platform Strategy and Design
  Graduate Prerequisites: QST PL727 or PL730, QST SI750 or SI751, or permission of instructor
  To thrive in the modern economy, managers, entrepreneurs and investors need a thorough understanding of platform businesses. Indeed, today's most powerful and valuable firms, from Airbnb, to Amazon, Facebook and Salesforce, operate as platforms connecting buyers and sellers, or users and advertisers, or users and third-party developers. These platforms derive their value from network effects and the ability to harness innovation from their users. Drawing on cases from social media, entrepreneurship, enterprise software, mobile services, and consumer products, we will analyze and learn to launch platform startups, convert existing businesses into platforms, and compete in a platform-centric world. Students will learn to apply concepts from industrial economics, market design, and game theory to real problems.
• QST IS 828: Managing Information Security
  Graduate Prerequisites: IS710/711/716
  This MBA elective (also open to undergraduates) will combine a technical and business approach to the management of information. It will address technical issues such as cryptography, intrusion detection and firewalls along with managerial ideas such as overall security policies, managing uncertainty and risk and organization factors. We will examine different aspects of computer security such as passwords, virus protection and managing computer security in dynamic environments. Topics will also include network security and how to secure wireless application and services. These technical details will be placed in a business context. The class will have a practical focus as we examine current best practices. There well be several guest speakers in the security area. This will be a project oriented class and students will present their research projects during the last several classes.
• QST IS 833: Introduction to Data Analytics in Python
  Graduate Prerequisites: MSDT Students Only; IS717 or equivalent Python experience
  This course will introduce students to programming-based tools and techniques for becoming analytically-minded managers. The course covers both a hands-on introduction to the concepts, methods and processes of business analytics as well as an introduction to the use of analytics as the basis for creating a competitive advantage. We will review variables, data types, conditionals, loops, and functions, and use these to introduce data structures, including DataFrames. We will also cover reading and writing raw files and the core APIs in analysis and visualization. With the basics under our belt, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for reporting. These packages will facilitate workflow and enhance the basic Python functionalities. Using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. Throughout the final project, we will learn to extract value from data by asking the right questions and using the appropriate analytical methods and tools. These methods comprise data preprocessing, explanatory analysis, and machine learning techniques. Prior programming experience in Python is required.
• QST IS 834: Introduction to Python for Data Analytics
  Graduate Prerequisites: Not open to MSDT students (except as a substitute for IS833 with permission)
  This course will introduce students to programming-based tools and techniques for becoming analytically-minded managers. The course covers both a hands-on introduction to the concepts, methods and processes of business analytics as well as an introduction to the use of analytics as the basis for creating a competitive advantage. We will cover variables, data types and data structures, DataFrames, conditionals, loops, and functions. We will also cover reading and writing raw files and the core APIs in analysis and visualization. With the basics under our belt, we will complement it with some of the most popular libraries for data analysis in Python, such as Pandas and Numpy for data manipulation, Matplotlib and Seaborn for visualization, and Jupyter Notebook for reporting. These packages will facilitate workflow and enhance the basic Python functionalities. Using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. Throughout the final project, we will learn to extract value from data by asking the right questions and using the appropriate analytical methods and tools. These methods comprise data preprocessing, explanatory analysis, and machine learning techniques. No prior programming experience is required. Learning basic programming in Python is part of successfully completing the class.