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Data: Identify technological frameworks for collecting, preparing, processing, analyzing, and delivering data.
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Skills: Develop advanced analytical modeling and problem-solving skills to best address challenges in various industries.
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Reporting techniques: Learn reporting techniques with emphasis on visual display of big data and analytical results.
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Communications: Learn how to effectively communicate analytical and complex results to different audiences.
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Management skills: Develop core management skills relevant to business analytics projects, including designing, planning, implementing, leading teams and managing conflicts.
Learning Outcomes
Knowledge
On successful completion of this program the graduate will be able to:
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Identify technological frameworks for collecting, preparing, processing, analyzing, and delivering data.
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Recognize the challenges of implementing business analytics solutions, including strategic alignment, planning, project management, team leadership, conflict resolution, negotiation, and convincing techniques.
Competence & Skill
On successful completion of this program the graduate will be able to:
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Clean data.
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Analyze data.
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Effectively communicate complex analytical results and insights to a mixed audience.
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Exhibit advanced analytical modeling and problem-solving skills to best address challenges in various industries.
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Exhibit core management skills relevant to business analytics projects, including designing, planning, implementing, leading teams and managing conflicts.
Responsibility and Autonomy
On successful completion of this program the graduate will be able to:
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Apply advanced analytical models and software tools to address various types of business analytics problems.
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Recommend appropriate analytics solutions to business problems, including defining business requirements, relevant data, needed information technology, competitive edge, and value-added proposition to the business.
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Apply reporting techniques with emphasis on visual display of big data and analytical results.
Program Requirements
For successful completion of the MSBA degree, students must complete all components of the program, which carry a total
of 90 ECTS over 3 terms. The program consists of:
| PROGRAM REQUIREMENTS | ECTS |
|---|
Compulsory Core Business Courses
| 96 ECTS |
Two Options:
| 30
|
Option 1:
• 3 Elective Courses &
• Capstone Project
OR
|
27 ECTS
9 ECTS
|
Option 2:
• 2 Elective Courses &
• Research Thesis
|
18 ECTS
18 ECTS
|
| Total ECTS | 90
|
For a complete list of degree requirements, refer to the
Office of the Registrar Business Analytics Degree Requirement page.
Sample Study Plan
For a sample study plan that shows how a typical MSBA student may progress through the program, refer to the
Sample Study Plan published on the Department’s page.
MSBA 500 Business Understanding in Analytics9 ECTS
This course will focus on the business understanding and problem framing. This includes analysis of previous findings; identifying stakeholders’ challenges and organization eco-system; understanding innovation essentials and components of analytics framework to compete on analytics; developing a data strategy for defining key performance metrics, data quality checks, benchmarking indices, and data sources; introducing big data concepts and technological infrastructure for processing information; discussing innovative business models, appropriate analytical tools and necessary leadership role to implement analytics initiatives and prioritize them for budgeting; efficiency in a business domain. First, the course will establish that business analytics is distinct but related to analytics in general and that the distinction is the focus of the overall course as well as the whole MSBA program. Second, this course will familiarize the students with key notions in business, e.g., strategy, operations, and marketing vis-à-vis business analytics. Third, the students will be introduced to a framework of how to devise analytics solutions to business problems. Fourth, the course will demonstrate how analytics can be applied and improve business situations through specific industry and company cases.
MSBA 501 Data Processing Framework9 ECTS
The course focuses on the technology processing of data prior to performing data analytics to extract actionable intelligent insights. It covers data preparation, integration and processing using open-source software tools such as Python, Hadoop and Spark based platforms. Topics include identification of the datasets of interest; preparing the data; building data models using SQL and NoSQL databases and performing operations to explore large and complex datasets. It also explores big data and how and when to integrate big data platforms within an enterprise information system. Through guided hands-on tutorials, students will become familiar with data processing techniques using different frameworks.
.Prerequisite: MSBA Bootcamp.
MSBA 502 Applied Statistical Analysis9 ECTS
Business decisions are often too complex to be made by intuition alone. We need to communicate the structure of our reasoning, defend it to adversarial challenge, and deliver presentations that show we have done a thorough analysis. We also need to understand and make use of various sources of data, organise the inputs of experts and colleagues, and use state-of-the-art business software to provide analytical support to our reasoning. The overall objective of this course is to equip students with analytical thinking and powerful tools that help them be more effective in these tasks. The emphasis is not on building black boxes that deliver the right answer for each problem. Instead, the goal is to teach students how to use data to ask questions, build simple but powerful models that test their intuitive reasoning, improve managerial thinking, and facilitate the communication of their recommendations.
Through a combination of lectures, real-life case studies, computer workshops, and discussions students will develop specific skills in the area of data analysis for decision making, but more importantly, become more informed and critical users of these tools. By the end of the course, students should be able to identify the areas where data analytics can add the most value, select appropriate types of analyses, and apply them in a small-scale, quick-turnaround but high-impact fashion. The course is multi-disciplinary in nature and adds to the analytical dimension of other areas, including finance, operations management, marketing, and accounting.
MSBA 503 Optimization & Simulation9 ECTS
This course is an introduction to quantitative models for managerial decisions making in a complex and dynamic business environment. Students learn to develop linear, discrete, non-linear, and multi-criteria optimization models, perform sensitivity analysis, develop constraint programming models, analyze decisions under uncertainty, and conduct scenario analysis using simulation. The course relies heavily on the use of Excel and R’s lpsolver.
MSBA 601 Data Visualization & Communication9 ECTS
This course introduces students to the latest data visualization techniques and tools to visualize data using dashboards, scorecards, and other formats. Students will learn presentation techniques with emphasis placed on the data story, the visual display of data, and smart reporting of results. Students will acquire hands-on skills to create effective information visualization based on the different data types and audience. A mix of coding with out-of-the-box tools will be explored depending on the visualization goals and context.
MSBA 602 Predictive Analytics & Machine Learning
9 ECTS
Students in this course will learn about supervised and unsupervised training methods. The focus is on identifying relationships that cannot be found by basic statistics and used for example in customer satisfaction, branding, machine failure, resource allocation, fraud detection, and fraudulent activities. Techniques include Nearest Neighbors, Naive Bayes, deep learning, text mining, clustering, association rules, regularization and dimensionality reduction. The bias/variance trade-off and model selection are a focal point of the course and will be illustrated from multiple angles. Students will acquire hands-on experience on all techniques taught. Prerequisite: MSBA 502.
Elective Courses
MSBA 504 Text Analytics and Natural Language Processing
9 ECTS
This course focuses on the computational aspect of Natural Language Processing (NLP) technologies and aims at finding a balance between traditional and modern NLP techniques. It covers major concepts and techniques for processing, cleaning, visualizing, and analyzing textual data to extract interesting information, discover knowledge, and support decision-making in business applications. Students will learn fundamental pre-processing techniques (i.e., tokenization, stemming, lemmatization, part-of-speech tagging, and named entity recognition), text representation (i.e., vector-space and language models, and modern distributed representation of words), and various text analytics tasks (i.e., text categorization and classification, document summarization, and sentiment analysis). Hands-on labs and projects in parallel to course lectures and readings will allow students to develop practical skills in building foundational NLP tools that can be applied to address real-world business analytics problems.
MSBA 505 Venture Acceleration Practicum9 ECTS
Students will learn about the lean startup approach to new products and new venture development process as well as associated business model concepts while getting hands-on experience through the actual doing of new startup/venture idea acceleration. The structure of the course provides for current entrepreneurs to mentor students in action. The entrepreneurs understand that class participants may have skill gaps and a nascent understanding of the skills they need. Thus, they will provide students with invaluable tips, tricks, and traps of entrepreneurship as well as know-how.
MSBA 506 Supply Chain Management9 ECTS
This course addresses supply chain management as a source of competitive advantage. It covers procurement, logistics, inventory management, warehousing, network design, and information communication in the context of the supply chain. Emphasis is placed on improving the performance of the supply chain through coordination strategies and the use of analytical tools. Case studies and discussion of current developments form an integral part of the course.
MSBA 507 Operations Management9 ECTS
This course aims to present to the students how to design and manage operations in an organization for a sustainable and competitive advantage. The course addresses theoretical and practical insights into service and manufacturing operations, in both the private and public sectors. The course covers topics such as: forecasting; strategic operations; aggregate planning; inventory management; MRP, ERP and scheduling.
MSBA 603 Data-Driven Digital Marketing9 ECTS
Digital marketing in the era of fast-browsing, redundancy of choices and lack of time has quickly evolved into a challenging science of perception, with data as its core driver. This course covers the key concepts and strategies of data-driven digital marketing and growth hacking with real-world applications and case studies. The aim is to demystify the role of data in providing critical marketing insights that can pave and shape marketing strategies. Students will examine the various techniques for search engine optimization and will learn how to implement and manage search-advertising campaigns. They will also learn how to effectively engage with customers across a diverse range of social media platforms and experience the best practices for creating and delivering effective e-mail and mobile marketing campaigns. The course utilizes relevant theory, empirical analysis, and practical examples to develop the key learning points.
Prerequisites: MSBA 500, MSBA 501, MSBA 502.
MSBA 604 Healthcare Analytics9 ECTS
The rise of preventive care, health technology and telemedicine has generated massive amounts of multidimensional health data. The magnitude and complexity of these data are overwhelming for healthcare providers and stakeholders to analyze and extract meaningful knowledge to make informed decisions. Moreover, the COVID 19 pandemic has unveiled profound weaknesses in the healthcare systems of most countries. Global investments in private health systems and private healthcare solutions have witnessed a 6% increase in Q2 2020 and are predicted to increase significantly in the future.
The expected digital transformation will not be possible without data and analytics. In this course, students will be equipped with the knowledge to work in the healthcare field or with a healthcare client as an analyst or consultant. Students will be introduced to the pillars of healthcare systems and the main health concepts and measures. They will learn about healthcare data types and sources, how to formulate data queries, how to use geospatial information systems to map health data, and how analytics is applied in the healthcare field. Finally, students will dive into the economic evaluation and financial impact of health-related interventions and programs.
Prerequisites: MSBA 602.
MSBA 605 Forecasting Analytics9 ECTS
Time series forecasting is essential for every organization that deals with quantifiable data. It is widely used in retail stores, international financial organizations, energy companies, banks and lending institutions, and in many other industries. Forecasting analytics enable managers and policy makers to better make informed decisions. This course is a hands-on introduction to quantitative forecasting of time series. Students will learn the most popular forecasting techniques used in practice. The course covers topics such as pre-processing, characterization, and visualizing time series, model performance evaluation, smoothing methods, time series regression models, Box- Jenkins models, autoregressive integrated moving average (ARIMA) models, models with binary outcome, and neural networks for time series (if time permits).
Prerequisites: MSBA 502.
MSBA 607 Big Data Processing and Blockchain Technology9 ECTS
This course is an extension to MSBA 501 Data Processing Framework and has two pillars. The course first focuses on blockchain technology and its applications in business. It explores how blockchain brings profound changes to businesses and explains how it transforms businesses structures, functions and roles of the organization. The course then dives into the various methods of blockchain governance that exist in the marketplace and examines specific features of blockchain to overcome problems that have been difficult to solve in the past using the existing centralized architecture. Topics include key concepts like hashing, public key cryptography, digital signing, mining, proof-of-work, proof of stake, public vs private vs permissioned blockchain, peer-to-peer transactions, blocks, consensus mechanisms, smart contracts, crypto-asset, distributed resources, decentralized protocol, and the double-spending problem. These concepts will be illustrated using the Bitcoin application and implemented mainly using Ethereum. The course then tackles how to process large data volumes on large computational clusters by introducing advanced features for Spark 2.0. Students will learn how to set up clusters in both batch and real time modes, retrieve big volumes of textual data, analyze streaming data, and use the ML API.
Prerequisites: MSBA 501, MSBA 601.
MSBA 608 Capstone Project9 ECTS
The Capstone Project allows students to work on real-world business problems using data, analytics, and statistics. Graduate students work with a faculty supervisor and a supervisor/mentor from the company to gather/collect data, model, analyze, and recommend a solution for a significant business program. The capstone is typically a substantial project (often spanning one or two terms) where students tackle a significant business analytics problem end-to-end. Students are expected to demonstrate core competencies (e.g., data mining, modeling, visualization, etc.) and integrate knowledge from across the program. The end deliverables include a comprehensive report and a formal presentation that detail the problem, the analytical approach, and the recommended solution. This is not a theoretical exercise – the scope should be feasible yet challenging, with clear business objectives and measurable outcomes. The three Capstone types are a corporate capstone with a company, a capstone topic proposed by a professor, or a case study.
MSBA 609 Research Thesis918 ECTS
The purpose of this course is twofold: The first is industry-oriented, focused on preparing students for the market and to hit the ground running from their first day on the job. The second is designed to enable students to deepen their knowledge in the field with the option of pursuing an advanced degree. In both cases, students will follow the entire lifecycle of framing, modeling, analyzing, and communicating results to address a business challenge and present their findings in front of a jury panel composed of academics and industry professionals.
