The Athens University of Economics and Business MSc in Business Analytics program covers in detail theoretical concepts on business, statistics and data management, while it recognizes the importance of practical training on systems and tools.
Program’s structure & philosophy
Several factors have been taken into consideration to structure the content of the program:
- existing programs in business analytics and data science in business schools and engineering/CS departments at well-known universities worldwide,
- proposals and suggestions of members of the advisory committee of the program, consisting of university professors and industry experts in the US and Asia,
- evaluations, comments and feedback from the participants in AUEB’s seminars and specialization programs on Big Data and Business Analytics during the last two years.
In brief, the program covers in detail theoretical concepts on business, statistics and data management, while it recognizes the importance of practical training on systems and tools. In addition, special care has been given to the “breadth requirement”: exposure on analytics applications in different fields and domains. The result is a well-balanced program between theory and practice. Theoretical concepts account for 50% of the program, systems and tools account for 25% of the program and the “breadth requirement” accounts for another 25% of the program.
Theoretical concepts fall into four broad thematic areas:
- Business Environment and Processes (Information Systems & Business Process Management, Enterprise Information Systems, Innovation and Entrepreneurship, Privacy and Data Protection)
- Statistics (Statistics for Business Analytics I, Statistics for Business Analytics II)
- Data Management (Data Management & Business Intelligence, Big Data Systems)
- Optimization and Knowledge Discovery (Large-scale Optimization, Mining Big Datasets, Social Network Analysis & Social Media Analytics)
Practical training on system and tools involve the following platforms: IBM, SAS, R, Hadoop and related projects, Spark, MongoDB, Redis, Neo4j, Python (tentatively).
Finally, case studies will be presented in the context of finance, marketing, health, energy, human resources, transportation, supply chain analytics.
Goals & Expectations
The goal of the program is to prepare students to get involved upon completion of the program in the design, implementation, and deployment of real analytics applications. To achieve so, the program involves courses in the areas of business, data management, statistics, machine learning, optimization, and visualization, combined with rigorous training on systems and tools. However, special emphasis has been given to the “domain expertise” dimension of the program: most data scientists agree that exposure to analytics implementation in different sectors is probably the most valuable skill of a data scientist. As a result, a full course, managed by leading industrial partners, is devoted to real case studies on health/insurance/energy/human resources/public sector/transportation/supply-chain analytics. Graduates of the program should be able to use theoretical concepts and analytical tools to efficiently and productively manage and analyze the information in a fast-paced, constantly-changing, data-rich universe.
Applicants’ Profile & Requirements
The program is seeking competent, self-motivated individuals with strong quantitative skills. To apply to the Master of Science in Business Analytics program, applicants must have a bachelor’s degree. All fields will be considered, but management science, business administration, mathematics, physics, statistics, engineering and computer science seem a natural fit for the program. Some knowledge on basic IT concepts, such as basic programming, is assumed. The student population is expected to be bi-modal: some students will be skewed more towards technology and others more towards business. This is a challenge (to keep a good balance between the two) and an opportunity (to make them learn from each other) at the same time.
All applicants should have demonstrated academic success as evidenced by undergraduate and graduate courses and grades. The admissions process is meticulous and selective, but also considerate of the candidate’s skills, competencies, and accomplishments as a whole.
The requirements to apply include a bachelor’s degree, recommendation letters, and proficiency in the English language. GRE or GMAT scores are strongly suggested only for the full-time program. Working experience is preferred, but not required for the part-time program.
On Business Analytics, Big Data and Data Science
“Data, data everywhere!” the Economist was proclaiming in a special issue a few years ago. Since then, terms such as “Business Analytics”, “Big Data” and “Data Science” became mainstream, with extensive coverage in newspapers, magazines, television shows – even global economic forums. The emergence of sophisticated web applications, the proliferation of social networks, the massive deployment of sensor networks and other data-producing applications have led to an exponential growth of data volumes, unforeseen just a few years ago. At the same time, the incorporation of a variety of data formats (traditional databases, text, audio, images, video) into mainstream data analysis, along with the velocity aspect of modern applications, radically revise the fundamental aspects of a decision-making process in private and public organizations. As Wired Magazine has pointed out a few years ago: ” The quest for knowledge used, to begin with, grand theories. Now it begins with massive amounts of data.”
Both Europe and the US are actively promoting a shift to data-driven economies. The European Commission is calling on national governments to “wake-up to this big data revolution” and the Office of the President of the United States regularly announces huge research initiatives on “Big Data”. Most experts agree that competencies in Business, Statistics and Computer Science will shape a new profession, the “Data Scientist”. As Tom Davenport puts it in one of his recent articles in Harvard Business Review, the data scientist will be “the sexiest job of the 21st century.” Someone who will be able to discover the “golden nuggets” hidden under massive amounts of data. All major consulting firms, such as Gartner and McKinsey, predict a great demand for such professionals in the next few years. At the same time, they identify the severe shortage of skilled people in that field. As a result, industry and academia alike are heavily investing on that field.
Athens University of Economics and Business, as one of the most extrovert and excellence-oriented academic institution in Greece, has identified this trend as early as 2011, crafting a state-of-the-art curriculum. By offering a short-term seminar and a long-term specialization program on Business Analytics and Big Data during the last two years, AUEB obtained the necessary expertise for a successful Master of Science program. AUEB’s Master of Science in Business Analytics is the first such program in Greece and among the first worldwide.
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Last updated January 16, 2018