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Companies (and consumers alike) are drowning in data. We have smart home automation of everything including heating, lighting, fridges, toilets and multi-media. Industrial robots. Social media. Virtual showrooms. 3D glasses. Eye-tracking for assistive communication. Quickly evolving technologies and consumer habits provide companies with data in higher volume, higher variety and higher velocity than ever before. With companies increasingly competing on data-driven business models, it is obviously convenient to have lots of data, but the real question is how to extract value from it to support decision making in strategy, marketing, finance, operations, and other areas of business.
In order to unlock the value inherent in data, companies need managers who combine business domain knowledge with solid methodological skills. This is the essential premise of the Master in Management Data & Business Analytics concentration, which equips students with a state-of-the-art toolkit to solve business problems with real-world data. The concentration consists of six modules:
Together, the 6 courses provide a holistic picture of how business analytics is used in practice to tackle challenging (data-rich) problems. Starting with issues related to the acquisition and generation of data (i.e., the groundwork of all data analyses), the concentration quickly moves on to introduce state-of-the-art optimization methods, simulations, and algorithms to analyze complex data structures. Besides the methodological skills that the courses convey, there is also a strong emphasis on providing students with hands-on computational and number-crunching skills so that students will be able to rigorously measure and analyze large-scale datasets, and then translate their findings into actionable managerial recommendations. But how to communicate these recommendations (and their implications) to senior managers; particularly so if these managers are not overly involved in data science?
Although oftentimes neglected, this is one of the most challenging issues in the practice of business analytics. The answer rests in profound data visualization and storytelling skills that greatly facilitate the communication between data analysts and senior management. Eventually, as the highlight of the concentration, students will face the Applied Analytics Challenge, which presents them with a complex and data-rich real-world business problem that they are supposed to solve. This unique challenge allows students to test their methodological and computational skills, and asks them to clearly articulate the managerial implications of their analysis.
The six modules span problems from all functional areas of business, and focus sharply on the practical side of business analytics. Each module provides the required technical background, and offers students plenty hands-on learning opportunities through case studies and technical exercises. Software used in class includes both standard office applications and various specialized packages.
Furthermore, students can apply and further deepen their skill set by choosing from various elective modules, such as “blockchain”, “business process engineering”, “human and machine predictions”, or “artificial intelligence for managers”.
The Data and Business Analytics concentration is suited for students interested in careers broadly defined around the term “data science”, and a useful complement to students that want to work in any functional area of companies that compete on data analytics and evidence-based decision-making. If you like data, are interested in advanced methods to extract business value from it, and are intrigued by business questions, this concentration is for you.
Co-Author: Prof. Dr. Jochen Schlapp is NORMA Group Associate Professor of Operations and Technology Management at Frankfurt School.
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