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Master in Data Analytics & Management
60 ECTS
On-campus participation is mandatory
*excl. 350 EUR enrolment fee
Master in Data Analytics & Management
The Master in Data Analytics & Management programme empowers you with the skills and competencies to lead data-driven organisations through digital and business transformation. Managers are required to foster such purpose-driven innovation and motivate organisational change through new and disruptive technologies. You will acquire skills in big data, digital transformation, disruptive/new business models, communication and leadership, which are all required to manage digital transformation in an ever-changing world.
Highlights
- Explore a flexible part-time master's programme with a dynamic dual format, including block weeks and self-study, designed for compatibility with full-time employment
- Engage in an English-taught programme that fosters a diverse cohort, bringing a variety of perspectives to the learning environment
- Acquire both technical and strategic skills to effectively lead data-driven organizations
- Benefit from lecturers who specialize in state-of-the-art scientific knowledge and have extensive experience in managing digital transformations
- Connect with an extensive network of industry experts and potential employers
Learning Goals
LG 1 Expert Knowledge and Comprehension of Management and Data Analytics to Drive Innovation and Transformation
Graduates will have an in-depth knowledge and a critical understanding of the key theories, methods and techniques to identify, analyse and implement business and digital transformation processes. They will have a profound knowledge of the parameters and instruments necessary for driving innovation and transformation.
LG 2 Usage and Development of Knowledge of Data-driven Innovation and Processes
Graduates will analyse the business' status quo and design creative solutions for data-driven innovation and business transformation. They will consult businesses professionally and proficiently.
LG 3 Effective Communication and Cooperation
Graduates will be effective communicators and project leaders in practical business contexts. They will write, present, discuss and defend research-based findings in interdisciplinary fields of research. Graduates will contribute to team performance.
LG 4 Professionalism and Self-Image
Graduates lead and support data- and purpose-driven innovative business transformation. They will base their professional activities on in-depth theoretical and methodological knowledge and they will develop these further. They have a thorough and critical understanding of their ethical and legal responsibilities. They will reflect upon their decision-making processes.
ECTS
The total amount of Credit Points (ECTS) to be earned with this programme is 60. An additional 60 Credit Points can be awarded by Frankfurt School for up to two years of relevant postgraduate work experience.*
Please take into account that persons interested in pursuing a doctoral degree in Germany must have accumulated at least 300 ECTS until the completion of their master's studies (exceptions might be made on a case-to-case basis by admission committees). This requirement is not relevant for professional practice.
*Proper documentation is required in a detailed confirmation letter from the employer.
Requirements
- A first academic degree* (Bachelor, Diploma or equivalent)
- Minimum one year of relevant post graduation work experience
- Sufficient written and spoken English skills** (TOEFL - 90 iBT / IELTS 7.0 or equivalent)
- Successful participation in our admission interview
* Applicants without a first academic degree must pass an eligibility assessment and demonstrate knowledge equivalent to a relevant first university degree for their intended course of study.
** Language proficiency waivers may apply to candidates with a prior degree in English, spent one year studying or working in an English speaking country or employment with English as the primary language (employer confirmation needed).
Target Group
Managers and young professionals from any industry with an interest in new technologies or going through digital transformation, consulting companies.
Ideal part-time master in Data Analytics & Management candidates:
- hold a first academic degree and have at least 1 years of postgraduate work experience in a relavant field
- have the ambition and motivation to work full-time and study part-time
- pursue clear career goals that can be reached with a master in Data Analytics & Management (i.e. digital transformation, career development or/ and career change)
- want to develop their data analytics expertise, enhance their leadership skills, and expand their professional networks across different industries
- hold a EU citizenship or EU resident permit
Visa
Please be aware that our Part-Time Master in Data Analytics & Management programme is designed for individuals who already possess the right to reside and study within the EU.
Consequently, we are unable to support student visa applications for this specific programme. Applicants requiring a student visa are encouraged to explore our Full-Time Master Programmes, which is eligible for student visa support. We advise all prospective students to carefully consider their visa status when applying to ensure alignment with their educational pursuits.
Meet us Online and On-Campus
Learn more about our Master programmes at one of our Master Info Evenings and find out which programme could help you excel in your career.
You may also come and explore our campus and speak to representatives from our master's programmes face-to-face, at one of our Open Campus Nights.
This programme will teach you how to utilise data to transform a business model into a data and purpose-driven organisation. In order to do so, step one is to cover the technical background such as machine learning, IoT, Blockchain, data visualisation and collecting and aggregating data. In a second step, we proceed to translate how such technologies advance and transform a business model as well as to identify the business’ strategic implications, organisational transformation and opportunities. The third step builds on the human aspect of digital transformation: leadership constitutes a vital component in achieving purpose-driven and sustainable change management.
Data Bootcamp
This block week provides insights into the technical foundations of collecting, managing and validating data. It gives you an introduction to IoT sensor technologies and their integration into data-collecting infrastructures. You will also study big-data infrastructure solutions of the tabular and unstructured types (e.g. Spark), graph databases (Neo4j) and object stores. In the blockchain part, you will learn how blockchains are created through a decentralised database with a consensus algorithm and how to programme a basic smart contract.
If you do not have any experience in Python programming, one of the following two classes will be a pre-requisite for completing this module: coursera or udemy.
Lecturers: Istvan Szukacs & Levente Szabados
IoT
Collecting, Aggregating &
Managing Data
Blockchain
Machine Learning Bootcamp
In this blockweek you will focus on the most fundamental techniques of data acquisition and data cleaning as well as data preparation for exploratory analyses. You will study how to use the tools of the Python ecosystem to create visualisations and thus draw insights from descriptive statistics for business decision-making. You will also learn about the basic tasks of machine learning: clustering, classification and regression methods. We will introduce you to deep neural networks and a high-level summary of convolutional and recurrent network methods. The module finishes with a summary of basic ecosystem elements like Dashboard and API tools for the deployment of machine learning.
If you do not have any experience in Python programming, one of the following two classes will be a pre-requisite for completing this module: coursera or udemy.
Lecturers: Levente Szabados / Jan Nagler
Data Visualisation & Data Science
Machine Learning & Deep Learning
Deploying Machine Learning
Disruptive Business Models
The third block week builds on the previous 2, covering how the abundance of data and the advancement of algorithms is harnessed to generate competitive advantage. The first part of the module gives you an overview of the new types of business models that are emerging based on data and machine learning and shows how existing business models are affected by digitalisation. In the second part of the module you will have the chance to apply this knowledge to concrete use-cases and derive implications for your organisation. A particular focus will be on how platform economics are becoming increasingly important for the generation of sustainable business models.
Lecturer: Jochen Schlapp & Dejan Juric
New Business Models
Platform Economics
Innovation Management
Business Model Optimisation
This block week focuses on using digital strategies to optimise the existing business model. Participants take a closer look at how data and patterns inferred from such data can harness the existing organisational strategy. As part of the module you will identify high-impact use-cases for your company that can be implemented with existing tools and solutions. You also get to know what this implies for how decisions are made on an everyday basis and how strategies are implemented by a new way of distributed and data-driven decision-making throughout the organisation.
Lecturers: Gyula Kovács & Levente Szabados
Identifying Opportunities
Building Organisational Capabilities
Agile Methodologies and System Thinking
Organisational Transformation
How can digital transformation be promoted within one's own company and how can management get employees on board? In this block week you will learn how to structure an organisation to facilitate data-driven organisational decision-making. You will learn about maturity models, change curves and playbooks (that we use in the AI course) and how to bring on board organisational stakeholders to create sustainable organisational change.
Lecturers: Markus Fitza, Gergely Szertics & Anna Langfalvy
Design Thinking
Leading Digital Transformation
Purpose & Data-Driven Change Management
Experiential Learning
tba
Data-Driven Management
Choose one Dedicated Elective
Digital Strategy
This module is concerned with the ethical, legal, and social implications of data science and advances in information technology, as well as the future of such advances. Participants will gain an in-depth comprehension of ethical and legal issues surrounding the work of data scientists and emerging information technologies, as well as the crucial ethical and legal questions that we should ask about such technologies. They will also think about the wider social implications of such technologies. The ethics part of the course investigates current ethical issues concerning data science: why we should care about ethics of data science, why privacy is important, the problem with algorithmic bias, as well as ethical dimensions of project design and deployment in data science. The legal part of the course offers an introduction into the GDPR. The rest of the course takes a look at the future of AI and the social and ethical dimensions of that future.
Lecturer: Sebastian Köhler
Blockchain in Business
Students are introduced to token economy, blockchain as a service, blockchain-based software products, and peer-to-peer blockchain models. The approaches that are used to meet environmental, social, and governance goals with blockchain are illustrated. The design of CBDCs and various variants for a digital euro or the digital dollar in real-life is touched on. Topics such as interoperability amongst blockchain networks and hybrid blockchains and their implications for business are contained. Further examples that are subject to this module comprise instant cross-border transfers, real-time settlements on stock exchanges, and blockchain as an ‘electronic notary’. Limitations of current blockchain projects and the meaning of scalability for broad adoption, possibilities regarding IoT, and real-life pilot projects are outlined to the students. Future applications of blockchain technology such as identity management and distributed data storage are covered in this module.
No prior technical knowledge of blockchain or distributed ledger technologies is required. However, a basic understanding of business principles, economics, and a general comfort with technology would be
beneficial.
Lecturer: tba
Electives Info
Digital Strategy- This module is offered by the MSc MDAM program and has attendance restrictions for students from external programs.
Blockchain- This module is offered by the MSc MBDA program and has attendance restrictions for students from external programs.
Master's Thesis
Highlights
Study Structure
Thanks to the dual structure, alternating block weeks and self-study, the Master in Data Analytics & Management programme can be optimally combined with your professional activity. After the introductory week, the block modules take place once approximately every nine weeks, from Monday to Saturday at Frankfurt School. Between each intensive block week, you will work alone or in groups on study topics that you can choose to base on your own business, or on real-life cases.
You will then complete your studies with your six-month Master's Thesis and a final conference. Our lecturers and professors accompany you during both phases of study, providing guidance, advice and recommendations throughout the whole programme.
The Blockchain Center
The Frankfurt School Blockchain Center (FSBC) is a think tank and research center focused primarily on investigating the implications of blockchain technology. In addition to general research and prototype development, the FSBC serves as a networking hub for managers, start-ups, and experts to exchange knowledge and best practices. The FSBC also organizes educational opportunities for both students and executives, including on-campus courses, workshops, and conferences.
Currently, the FSBC is focusing on crypto assets, digital securities, the digital euro, CBDCs, tokenization of assets, decentralized finance (DeFi) and non-fungible tokens (NFTs).
Find out more about our Blockchain Center here.
The Centre for Human and Machine Intelligence (HMI)
The Centre for Human and Machine Intelligence (HMI) conducts basic and applied research at the intersection of Artificial Intelligence & Machine Learning, Decision & Social Science and Finance & Management. Our focus is to develop and advance our understanding of computational systems that augment human capabilities for judgment and decision-making.
Find out more about HMI here.
Rankings & Accreditations
Frankfurt School is one of the best European Business Schools. Accredited by AACSB, EQUIS and AMBA, the three leading international associations of business schools. Frankfurt School is one of the few institutions worldwide, which has been awarded the so-called "Triple Crown".
Learning Experience
Studying at FS
Whilst you will receive a strong theoretical foundation, the emphasis of the programme will be on the practical application of methods and theory. As such, a significant proportion of the modules involves teaching by practitioners, who have everyday experience with data-driven decision-making and digital transformation. Students will advance in critical thinking and problem-solving strategies, which in return enable them to apply the knowledge, skills, competences and methods for their businesses.
FS Alumni Community
As a student of our part-time degree programmes, all the Frankfurt School Alumni Network is available to you. Take advantage of the numerous advantages of the FS Alumni & Friends Network, exchange ideas and expand your professional and private contacts. We offer you numerous events and platforms for this purpose, such as workshops, lectures, continuing education programmes and numerous events.
Continuous Learning
Throughout your professional career, you will continue to develop personally and professionally. We would like to accompany you in this process even after you have completed your studies. As alumni, we invite you to participate in one module of your degree programme per year. That way, you can regularly refresh and expand your knowledge and skills.
Class profile 2024
| Number of students | 19 |
| Average age | 27 |
Network & Career
Career Growth Opportunities
Students participating in this programme aim at deepening and advancing their already sophisticated careers to the next level by adding innovative and revolutionary components, competences and methodology as well as objectives for their businesses. Our graduates are qualified to lead in areas such as IT- Consulting, Data-driven Management, Purpose-driven Management, digital transformation, business analytics, data analytics, change management, etc.
Connect with your Peers
Our students typically come from consulting and industry with an extensive range of practical and educational backgrounds which will open up your network to new areas. During the intensive block weeks you'll get the chance to exchange thoughts and learn from each other’s know-how and practical experience.
Connect with our Corporate partners
Additionally, our exclusive corporate and alumni connections allow you to strengthen your career network in a wide range of industries while studying. Our Frankfurt School Alumni Network brings together a large number of national and international executives at various events and workshops.
Career Services
Our exclusive corporate connections allow you to build a strong network for your career. Our Careers Services team is available to provide you with individual consultations on your career. Additionally, you benefit from our regular expert talks as well as the opportunity to work full-time throughout your part-time studies.
Application Process
The first step of your application process is to complete the online application form. You will need to upload the supporting documents listed below.
Once you have submitted your application with all the required documents, we will process your application. Successful applicants will be invited for an interview within a couple of weeks. That is the second step of the application process. The interview will be held through a video call. The purpose of the interview is to gain a better understanding of your professional and academic experience and discuss your motivations for the programme and goals for the future.
The third step is the Admission Committee, where members of Frankfurt School will get together and make a final decision on your application that will be communicated to you via email or phone. You can expect this final response within approximately 8 weeks after submission of a complete application.
Required Documents
- CV or resume in English
- Certified copy of your undergraduate transcript of records and degree award certificate
- Proof of English Skills, TOEFL - 90 iBT, 577 ITP / IELTS 7.0 or equivalent
- Proof of relevant professional experience
- Copy of your passport
Each of the documents listed above are required for completing your application. However, you do not need to upload them all at once.
Discounts and Deadlines
We admit candidates on a rolling basis and therefore encourage you to complete your application early. There are also financial advantages for candidates who complete their application early.
- Early Bird Discount (EUR 3,500): 31 May 2025
- Final Application Deadline: 15 September 2025
Financing
Investing in your future
Your degree is an investment in your professional future. As a business school of international standing, not only do we offer you ideal conditions for earning a degree – we also offer you excellent career prospects.
For this programme, Frankfurt School does not tend to offer scholarships, it happens only in rare cases for exceptional candidates, however there are other external funding options that you could consider to help support you financially. There are also different payment options to make the payments as comfortable as possible.
Contact
Tamay Kasap Ercanli
Recruitment Officer
Isabeau Köhncke
Recruitment Officer
