Management Information Systems

  • QST IS 841: Advanced Analytics For Managers: Data Mining
    Graduate Prerequisites: IS823 recommended
    The widespread proliferation of IT-influenced economic activity leaves behind a rich trail of micro-level data about consumer, supplier and competitor preferences. This has led to the emergence of a new form of competition based on the extensive use of analytics, experimentation, and fact-based decision making. In virtually every industry the competitive strategies organizations are employing today rely extensively on data analysis to predict the consequences of alternative courses of action, and to guide executive decision making. This course provides a hands-on introduction to the concepts, methods and processes of business analytics. We will learn how to obtain and draw business inferences from data by asking the right questions and using the appropriate tools. Topics to be covered include data preparation, data visualization, data mining, text mining, recommender systems as well as the overall process of using analytics to solve business problems, its organizational implications and pitfalls. Students will work with real world business data and analytics software. Where possible cases will used to motivate the topic being covered. Prior courses in analytics, data management and statistics (such as IS823) will be helpful but are not required.
  • QST IS 843: Big Data Analytics for Business
    Graduate Prerequisites: Python basics (e.g. IS717, IS834, QM877 (Python Bootcamp) or equivalent); Some prior experience with analytics (e.g. IS823, IS833, IS834, IS841, MK842, MK872, MK876); or permission of the instructor.
    This programming-based analytics course will cover how to perform statistical analysis of large datasets that do not fit on a single computer. We will design a Hadoop cluster on Google Cloud Platform to analyze these datasets. Utilizing Spark, Hive, and other technologies, students will write scripts to process the data, generate reports and dashboards, and incorporate common business applications. Students will learn how to use these tools through Jupyter Notebooks and experience the power of combining live code, equations, visualizations, and narrative text. Employer interest in these skills is very high. Basic programming in python, and basic analytics are prerequisite.
  • QST IS 853: Business Insights through Text
    Graduate Prerequisites: QST MK 842 or QST IS 833 or QST IS 834 or QST QM 877; QST MK842 or IS833 or IS834 or QM877
    Eighty to ninety percent of current exponential data growth is attributed to unstructured data such as text. Increasingly, the data has become more like crude oil that has to be refined and structured to extract value for business insights and strategies. Managers need to understand the opportunities and challenges associated with unstructured data for competitive advantage. In this class, students will learn what businesses can do with text data through a variety of case-based examples based on research and industry applications from Marketing, Information Systems, Finance, Strategy, and Social Impact perspectives. This is a course dedicated to understanding the potentials of text data in different settings curated based on Natural Language Processing (NLP) techniques involved. The focus of the course is on the substantive value of text and methods will be introduced as backdrops. Throughout the course, we will use Python, a powerful language and the main tool used by deep learning data scientists. However, skeleton codes will be provided to reduce technical burdens. 1.5 cr.
  • QST IS 854: Digital Strategy for Emerging Business Leaders
    Graduate Prerequisites: SI851 preferred
    A digital strategy is an organization's plan to leverage digital technologies to create new business models, products, and services, as well as to improve internal processes and interactions with customers, suppliers, and partners. For business leaders, a digital strategy is crucial to staying competitive and grow their businesses. In this course, students will learn how to design, execute and communicate digital strategies in a complex organization. We will also learn key management concepts such as project delivery, change management, as well as financial modelling of digital investments. In addition to case studies and class exercises, we will bring in industry experts to share their real-world experience. In lieu of a final exam, students will form into project teams to design, develop, present and gain buy-in for a specific digital strategy.
  • QST IS 855: Digital Transformation: Immersive Interactions and Insights at Silicon Valley
    Graduate Prerequisites: FT MBA: second-year standing. PEMBA: 36 credits of coursework.
    This course will be a one week intensive held in Silicon Valley. The course is designed to achieve two objectives. First, to develop an appreciation for the role of Silicon Valley in Digital Innovation and, secondly, to examine how digital innovations are impacting key shifts in specific sectors. Students will be placed into teams and be expected to develop specific insights as the basis to engage in interactions with corporate executives, alumni and follow classmates. Teams will also visit leading companies involved in each sector and develop and present their team's perspective on key digital trends and leadership challenges for their sector.
  • QST IS 858: Agile Project Management
    This course is designed to provide 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 agile development approaches and will be introduced to RALLY Project Management software, the leader in the industry for SCRUM. Students will learn to analyze requirements, create backlogs, schedule "stories" to be developed and delivered, hold standup meetings, and Retrospectives.
  • QST IS 878: Business Modeling with Spreadsheets
    This course aims to sharpen students' ability to frame a business problem and organize the relevant information in a way that is conducive to developing a spreadsheet model, and to perform logical analyses in an organized and rigorous fashion. Students will learn how to create a workable prototype of a spreadsheet based upon formula-charts, or a directed-graph diagram, applying principles of spreadsheet engineering to design the spreadsheet in a way that prevents errors. The course will teach students how to design, build, test, and use a spreadsheet, as well as how to process and visualize data in preparation for building a well-structured model. Students will be exposed to settings in which models can be used effectively. They will apply modeling concepts in practical situations and learn to extract insight from models and to use those insights to communicate, persuade and motivate organizational decision making. They will also learn how to formulate a constrained optimization problem with multiple variables for a variety of applications including, Strategy, Operations, Technology Management, Marketing, and Finance. The course will show how to understand how to use sensitivity analysis to evaluate the impact of a parameter on the optimal solution to a problem and cover the key principles for Real-Time Data Capture for Analytic. Finally, students will learn the latest technologies for effectively linking spreadsheets to relational data bases, and to reliably manage large scale spreadsheets. 1.5 cr.
  • QST IS 879: Business Modeling with Spreadsheets
    This course aims to sharpen students' ability to conduct quantitative analyses of business problems. The primary focus is on problem formulation and analysis -- identifying the key components of a decision problem, structuring it, translating it into a graphical chart, and then building the appropriate mathematical and spreadsheet models. These models are used to generate valuable qualitative and quantitative managerial insights. Students will be introduced to data management and decision tools such as Formula Diagrams, Linear Optimization, and Error Detection methodologies, as well as to Parametric Sensitivity Analyses. While each business problem is distinctive, a disciplined approach to problem solving can be incredibly useful across many career contexts. The concepts and exercises in this course will sharpen the student's professional ability to structure a messy problem and do some disciplined analysis on it. Developing these modeling skills requires the opportunity to brainstorm, reflect, and practice it on a wide variety of problems. Hence, the course includes intensive team-centered workshop sessions where all students get hands-on practice working with a group of peers to frame various problems in appropriate analytical terms, develop a solution approach, and critically reflect on the results. Examples will be drawn from Strategy, Operations, Technology Management, Marketing, and Finance to expose students to the broad applications of the concepts and tools learned in this class. Many of the up- to-the-minute Excel techniques covered in the course are now considered standard in industry, and developing a good understanding of them will deepen the student's ability to identify opportunities in which spreadsheet analytics can be used to improve performance, drive value, and support important decisions. Finally, students will learn the latest technologies for effectively linking spreadsheets to relational databases, and to manage reliably large scale spreadsheet development projects.
  • QST IS 883: Synthesizing Digital Efforts to Deliver Better Outcomes
    Graduate Prerequisites: MSDT Students Only
    Most organizations today -- of all sizes and stages of maturity -- are undertaking internally and externally focused digital initiatives. The success of these programs varies widely and depends on numerous strategic, tactical and technical factors. Foremost among them are how individuals with skills across strategy, design, product/project management, technology, and data science think individually and how they work together collectively. In this class, students will learn and apply leading thinking, practices, and tools used by top digital professionals to design and build digital products. The first half of the course will focus on cloud technology and its effect on organizational structures and product development lifecycles. In the second half of the semester, students will organize into teams to begin work on a digital experience they will design and iteratively realize the following semester in IS890, applying skills they have learned throughout the MSDT as well as new methods including exploratory ethnography, service design, agile/scrum, and data-driven experimentation.
  • QST IS 889: Data Management
    Graduate Prerequisites: Non-MSDT students only in Fall; MSDT students only in Summer
    The ability to collect, organize, access, analyze and harness data is a source of competitive advantage for some and a competitive necessity for others. Getting an organization to the point where it has a data asset it can leverage is a non-trivial task. Many firms have been shocked at the amount of work and complexity that is required to pull together an infrastructure that integrates its diverse data sources and empowers its managers. This course will provide an introduction to the concepts and technologies that are involved in managing and supporting the data assets of your organization. We will cover data modeling, relational databases, including SQL, data warehousing and business intelligence.
  • QST IS 890: Digital Transformation Through Experimentation and Scaled Agile: A Practicum
    Undergraduate Prerequisites: MSDT Students Only
    This course describes how digital transformation increases the reach and speed of experimentation, and how this in turn both improves execution and supports innovation. The course will examine how successful firms integrate modeling, data gathering, analysis, knowledge synthesis, with both their planning and operations. Managing for such an approach requires not just an agile, but a scaled-agile approach, with multiple parts of the firm co-evolving in a mutually supportive way. Working in small teams, students will apply the concepts to term-length projects. The class will run as an applied studio, with teams providing constructive feedback to each other throughout the term.
  • QST IS 898: Directed Study: Info Systems
    Graduate Prerequisites: consent of instructor and the department chair
    Graduate-level directed study in Management Information Systems. 1, 2, or 3 cr. Application available on the Graduate Center website.
  • QST IS 899: Directed Study: Info Systems
    Graduate Prerequisites: consent of instructor and the department chair
    Graduate-level directed study in Management Information Systems. 1, 2, or 3 cr. Application available on the Graduate Center website.
  • QST IS 912: Platform Strategy & Design
    This class will cover seminal works in the economics of information including the Nobel Prize winning ideas of Akerlof, Arrow, Spence, Stiglitz, and von Hayek. It will proceed through (i) concepts of information, its value and measurement (ii) search and choice under uncertainty (iii) signaling, screening, and how rational actors use information for private advantage (iii) how to price and package information goods (iv) how properties of information cause market failure (v) macroeconomic effects of information (vi) social and legal issues of owning information. Although primarily a theory class, it should be of interest to any student applying information economics in academic, commercial, or government policy contexts. Prerequisites are a graduate course in microeconomics and mathematics at the level of introductory calculus and statistics. Students will produce a major paper suitable for publication or inclusion in a thesis.
  • QST IS 919: Research Seminar 2
    This course covers those important Information Systems (IS) theories and topics that are at the organizational level of analysis and below. That is, it focuses on the behaviors of single individuals and small numbers of individuals, such as dyads and teams. This is consistent with an approach to organizational phenomena that distinguishes between micro and macro levels of research, this course being the micro. The focus is on ways that individuals and teams use information technologies to acquire, process, and transfer information, and the effects these technologies have on individual cognition and dyadic and group interactions. It also investigates the design and implementation of information technologies and the impact of these on organizational outcomes. The course is designed to engender students with a broad knowledge of research at the intersection of information technologies and organizations, with an emphasis on theoretical underpinnings and methodological choices.
  • QST IS 990: Current Topics Seminar
    For PhD students in the Information Systems department. Registered by permission only.
  • QST IS 998: Directed Study: Info Systems
    Graduate Prerequisites: consent of instructor and the department chair
    PhD-level directed study in Management Information Systems. 1, 2, or 3 cr. Application available on the Graduate Center website.
  • QST IS 999: Directed Study: Info Systems
    Graduate Prerequisites: consent of instructor and the department chair
    PhD-level directed study in Management Information Systems. 1, 2, or 3 cr. Application available on the Graduate Center website.