M.S. in Business Intelligence & Analytics And M.S. in Marketing Dual Degree Master's Program

This 2-credit course focuses on data and database management, with an emphasis on modeling and design, and their application to business decision making. The course provides a conceptual understanding of both organizational and technical issues associated with data. The central theme concerns data modeling and databases. We examine organizational approaches to managing and integrating data. Among the topics included are normalization, entity-relationship modeling, relational database design, SQL, and data definition language (DDL). Discussed are specific applications such as strategic data management, master data management, and physical database design. The course concludes with a brief overview of Decision Support Systems, data warehousing and business intelligence, NoSQL databases (e.g., MongoDB) and cloud computing. The course includes a number of cases studies and modeling and design projects. Students in MIS 631 must also enroll in the associated 1-credit lab course MIS 632 Managing Data Lab.

This 1-credit lab course provides an experiential learning component for MIS 631 Data Management for which it is a co-requisite. MIS 632 provides hands-on experience in designing, implementing, and querying data bases. The relevant software is introduced using demonstrations, in-class exercises and homework exercises that are closely tied to and executed in synch with the conceptual and theoretical material covered in MIS 631. Specifically, students will gain hands-on experience in: (i) ERWIN - a widely used commercial tool for representing conceptual (e.g., E-R diagrams) and logical data models (e.g., relational DBMS), (ii) PostgreSQL (relational database software), (iii) SQL Structured Query Language) and (iv) MongoDB a NoSQL document data store. Students in MIS 632 must also be enrolled in the associated 2-credit lecture course MIS 631 Managing Data course.

Corporate financial management requires the ability to understand the past performance of the firm in accounting terms; while also being able to project the future economic consequences of the firm in financial terms. This course provides the requisite survey of accounting and finance methods and principles to allow technical executives to make effective decisions that maximize shareholder value.

This course introduces basic methods underlying multivariate analysis through computer applications using R, which is used by many data scientists and is an attractive environment for learning multivariate analysis. Students will master multivariate analysis techniques, including principal components analysis, factor analysis, structural equation modeling, multidimensional scaling, correspondence analysis, cluster analysis, multivariate analysis of variance, discriminant function analysis, logistic regression, as well as other methods used for dimension reduction, pattern recognition, classification, and forecasting. Students will build expertise in applying these techniques to real data through class exercises and a project, and learn how to visualize data and present results. This proficiency will enable students to become sophisticated data analysts, and to help make more informed design, marketing, and business decisions.

This course covers basic concepts in optimization and heuristic search with an emphasis on process improvement and optimization. This course emphasizes the application of mathematical optimization models over the underlying mathematics of their algorithms. While the skills developed in this course can be applied to a very broad range of business problems, the practice examples and student exercises will focus on the following areas: healthcare, logistics and supply chain optimization, capital budgeting, asset management, portfolio analysis. Most of the student exercises will involve the use of Microsoft Excel’s "Solver" add-on package for mathematical optimization.

This 2-credit course focuses on the design and management of data warehouse (DW) and business intelligence (BI) systems. The course is organized around the following general themes: business value of data, planning and business requirements, architecture, data design, implementation, business intelligence, deployment, data integration and emerging issues. Practical examples and case studies are presented throughout the course. Students in MIS 633 must also enroll in the associated 1-credit lab course MIS 634 Business Intelligence & Data Integration Lab.

Prerequisite: MIS 634 CoReq

This 1-credit lab course provides an experiential learning component for MIS 633 ML Engineering 2 for which it is a co-requisite. MIS 634 provides hands-on experience in designing, implementing, and querying data warehouses and large-scale database systems. The relevant software is introduced using demonstrations, in-class exercises and homework exercises that are closely tied to and executed in synch with the conceptual and theoretical material covered in MIS 633. Specifically, students will gain hands-on experience in using: (i) Alteryx - a widely used commercial tool for the Extract-Transform- Load (ETL) function, (ii) ERWIN - a widely used commercial tool for representing conceptual (e.g., E-R diagrams) and logical data models (e.g., relational DBMS) and (iii) a NoSQL database (e.g., MongoDB). Students in MIS 634 must also be enrolled in the associated 2-credit lecture course MIS 633 Business Intelligence & Data Integration course.

Prerequisite: MIS 633 CoReq

This course covers fundamental topics in experimentation, including hypothesis development, operational definitions, reliability and validity, measurement, and variables, as well as design methods, such as sampling, randomization and counterbalancing. The course also introduces the analysis associated with various experiments. At the end of the course, students present a project, which consists of designing an experiment, collecting data and trying to answer a research question.

In this course, students will learn about marketing analytics techniques such as segmentation, positioning, and forecasting, which form the cornerstone of marketing strategy in the industry. Students will work on cases and data from real companies, analyze the data, and learn to present their conclusions and make strategic recommendations.

This course will focus on Data Mining & Knowledge Discovery Algorithms and their applications in solving real world business and operation problems. We concentrate on demonstrating how discovering the hidden knowledge in corporate databases will help managers to make near-real time intelligent business and operation decisions. The course will begin with an introduction to Data Mining and Knowledge Discovery in Databases. Methodological and practical aspects of knowledge discovery algorithms including: Data Preprocessing, k-Nearest Neighborhood algorithm, Machine Learning and Decision Trees, Artificial Neural Networks, Clustering, and Algorithm Evaluation Techniques will be covered. Practical examples and case studies will be present throughout the course.

Strategic Marketing - 16224 (3 ECTs)

This course will teach students to identify the objectives of the marketing function. Students will distinguish between the main instruments to diagnose a company's strategic position in the market and apply the knowledge to the company and market. Students will be able to list the concepts necessary to design a company marketing strategy.

Qualitative Methods and Survey Analysis - 16225 (3 ECTS)

This course will teach students to distinguish between the basic concepts and the methodologies to be carried out in each stage of market research (sample, questionnaire, data analysis, etc.). Students will solve a problem by designing the appropriate market study and apply the market research process to relevant marketing situations. Students will then analyze and evaluate the market research results and propose strategic orientations with operational actions.

Data Analysis in Marketing - 16226 (3 ECTS)

This course will teach students about marketing quantitative analysis, including types of marketing data, and inference analysis. Students will also learn about classical statistical inference, with a focus on distributional probability models, point and interval estimation, and hypothesis testing with maximum likelihood and extremum M-estimators. Additional topics include multiple linear regression analysis and nonlinear
regression, sampling techniques for finite populations, and practical implementation based on the use of specialized software.

Economics for Business - 16227 (3 ECTS)

This course will teach students to distinguish between the basic concepts of economic equilibrium under perfect competition and in contexts of market power. Students will identify the impact of economic activities and analyze the economic and organizational effects derived from contractual relationships between agents as well as the relationship between companies and the institutional framework in which they carry out their activities.

Consumer Behavior - 16228 (3 ECTS)

This course will teach students to distinguish between all the concepts related to market behavior in marketing management (strategic and operational marketing). Student will identify individual needs and motivations for purchasing various products and services, analyze the purchasing processes, and identify strategies for their application in a business environment. They will apply this knowledge along with internal and external consumer psychological variables in different commercial actions.

Marketing Management - 16229 (3 ECTS)

The aim of course this course is that Students develop personal managerial skills in "learning by doing" spirit. Students will compete playing on QUANTUM, a strategic marketing business game. QUANTUM is a marketing business-game for the development of practical skills in marketing management. It is based on the best analytical models for marketing decision making, combining academic rigor with manager's experiences in international markets. With this distinctive tool, the students learn concepts of product positioning, competitive strategy, new product development and life cycle forecasting, standardization or adaptation of products in international markets, sales promotion and loyalty programs, among others. QUANTUM is proprietary software, developed by a team of professors in Marketing Modeling at Universidad Carlos III: Mercedes Esteban-Bravo, Nora Lado Cousté, and Jose M. Vidal-Sanz.

Retail and Channel Management - 16230 (3 ECTS)

This course will teach students to distinguish between the management mechanisms of distribution channels. Student will identify the best strategic and operational decisions about the distribution channel chosen.

Market Analysis and Experimental Research - 16231 (3 ECTS)

This course will teach students to distinguish between the main instruments of experimental research to design a company marketing strategy. Students will prepare essential studies for the analysis of the perception of brands by consumers and apply the results of market studies to design company marketing instruments.

New Product Development - 16248 (3 ECTS)

This course will teach students to distinguish between the different instruments for managing new products. Students will apply the essential methods in the design and commercialization of new products to design company marketing strategies.

Pricing - 16249 (3 ECTS)

This course will teach students to distinguish between the different price management instruments. Students will apply the essential methods for the design of company price strategies.

Marketing SEO - 17831 (3 ECTS)

Student will learn about the different tools of search engine-orientated (SEO) marketing and apply SEO tools to improve marketing management.

Paid Digital Media - 17832 (3 ECTS)

Student will learn the different marketing instruments based on digital means of payment and apply digital payment instruments to improve marketing management.

CRM and Business Intelligence - 17830 (3 ECTS)

Students learns the importance of customer relationship marketing and applies the essential methods in the evaluation of customer management, and distinguishes between the best instruments for marketing and sales strategies.

Communication and Advertising - 16233 (3 ECTS)

Students will identify the objectives of the communication function in company decisions. The students will list the main communication instruments used to define a company operational strategy in the marketplace and apply advertising knowledge to the different strategies of the company.

Marketing Plan and Control - 16234 (3 ECTS)

Students will identify the objectives of developing a marketing plan and list the main instruments of a marketing plan. Students will then apply the controls to evaluate the strategies of the company.

Product and Brand Management - 17835 (3 ECTS)

Students will learn the different existing product and brand management instruments and apply the essential methods in brand management and product marketing to design brand strategies.

Digital Marketing - 17836 (3 ECTS)

Students will learn the latest trends in digital marketing and apply these techniques to improve operational strategies.

Digital Commerce - 17833 (3 ECTS)

Students will learn the different instruments of electronic commerce and apply these electronic commerce instruments to improve a company's marketing management.

Content Marketing and Social Media - 17834 (3 ECTS)

Students distinguish between the different elements of content marketing and direct marketing. Students then apply these learnings to identify business opportunities and establish marketing strategies through social networks.

Select 3 courses plus Master's Thesis.

Corporate Strategy - 16236 (3 ECTS)

Students will learn the different corporate strategic options and analyze the corporate strategies of a company related to the selection of businesses: diversification, vertical integration, internationalization, and restructuring. Students will also learn the different development methods based on internal and external growth (mergers and acquisitions), the basic foundations of business cooperation, and the fundamental role that strategic alliances play.

Sales Force and Key Account Management - 16237 (3 ECTS)

Students will learn the techniques for managing a sales force and how to apply the appropriate strategies for different sales functions.

Management Skills and Leaderships - 16238 (3 ECTS)

Students will learn how to use management tools to project manage, coordinate resources, and manage people. Students will analyze leadership from different approaches and styles in order to interpret the relationships between culture, leadership, and organizational results.

Advanced Topics in Marketing - 16242 (3 ECTS)

This course features advanced seminars on current issues (hot topics), such as Customer Relationship Management (CRM), Ethics and Social Corporate Responsibility in marketing, Health and pharmaceutical marketing, Social marketing, Logistics, Data Warehouse, and Business intelligence products, Impact of marketing actions in company stock market values, Luxury Marketing, Cross-cultural adaptation for multinational executives.

International Marketing and Trade - 17838 (3 ECTS)

Students will learn the different marketing instruments from an international point of view and apply the knowledge of international trade to management and marketing.

Marketing in the Services Sector - 17837 (3 ECTS)

Students will learn the different marketing instruments in the service sector and the particularities of the services from the marketing management point of view.

Master's Thesis - 16235 (6 ECTS)

The thesis is the culmination of graduate work. Students trained in the master's should demonstrate the knowledge, skills, and competencies acquired during their studies through an original thesis work about any specific problems of marketing and market research. Students should carry out individual work to demonstrate the knowledge, skills, and abilities acquired from their studies by solving specific marketing problems of companies in a business environment.