Master's program in
Big Data & Business Analytics

Master's Program Big Data & Business Analytics

1 st Year in India and 2 nd Year in Germany & Opportunity to earn approx € 36000 - € 48000 (Rs 28 - 38 Lacs) per annum

About the FOM University

Founded in 1993 by business associations, the state-approved non-profit FOM University has 29 Higher education centers in Germany. As a practice-oriented university for working people, the FOM promotes the transfer of knowledge between College and business. All courses offered by the FOM are tailored to the needs of professionals and trainees tailored.

The high acceptance of the FOM shows not only in the close co-operation with public universities, but also in Numerous cooperations with regional medium-sized companies as well as international corporations. FOM graduates have solid professional skills as well as outstanding social skills and are therefore very motivated by the economy desires.

  • With more than 46,000 students, ranked number 5 in Germany, 420 universities of applied sciences and universities as well as Germany's largest private university
  • Higher education centers in 29 cities in Germany
  • More than 1,900 full-time and part-time professors and lecturers Over 1,000 employees from 27 nations in consulting and administration
  • State recognized since 1993
  • Over 35 accredited programs
  • Accredited by the Science Council
  • System accredited: FOM's quality management meets the highest international standards (since 2012 quality seal of FIBAA, one of the most important agencies for evaluating universities)
  • One of the most research-intensive private universities of applied sciences in Germany (with 10 institutes, 13 competence centers and more than 500 publications per year)
  • Best Practice University of the German UNESCO Commission in the UN Decade of Education for Sustainable Development at universities
  • As the only private university member of the quality network "Dual Studies" of the Stifterverband für Deutsche Wissenschaft
  • 37 cooperative colleges worldwide
  • Carrier of the largest European study project in China
  • Over 800 corporate collaborations in Germany, including Siemens, Allianz, Ford, Bertelsmann, Telekom, BP, IBM, thyssenkrupp, Peek & Cloppenburg Dusseldorf, AOK, City of Munich, City of Dusseldorf

About the Program

What is the right time for a product launch? Which target groups should be reached? Should investment be made in new production facilities? Big data is becoming increasingly important in business practice: the amount of structured and unstructured data available to businesses today is growing rapidly - from finance to the healthcare industry. Big Data specialists span the spectrum from logic and quantitative methods through programming languages, frameworks and infrastructures to the interpretation and implementation of the results in the corporate processes.

Students are prepared to analyze and interpret large amounts of data and to derive recommendations for companies. Graduates can not only analyze data purely mathematically or statistically, but also evaluate it against a business background. They specialize in specialist and management tasks at the interface between IT, management and controlling. These can include positions as a Big Data Manager or Big Data Analyst, as Product Manager Data Integration, in Marketing as a Market Data Analyst or as a Data Scientist in Research.

Program Structure

Beginning of studies: April 2019
Duration: (1 & 2 Semesters) in India and (3 & 4 Semeters) in Germany + Thesis

Big Data Architecture & Infrastructure (Semester I)

  • Enterprise Architecture Management (EAM)
  • Technological requirements for Big Data
  • Vital infrastructures for data-driven business models
  • Complex processing by continuing
  • Data Categories

Big Data Analytics (Semester I)

  • Data sources and data categorization
  • Visual Analytics / Data Discovery / Exploratory
  • data analysis
  • AI methods such as machine learning
  • Computational Intelligence: fuzzy logic, neural
  • Networks, Evolutionary Algorithms

Decision-oriented management (Semester I)

  • Classical Decision Making
  • Management decisions from psychological view
  • Decisions in the strategy context

Scientific methodology (Semester I)

  • Qualitative and quantitative research methods
  • Quantitative data analysis (applications with R, statistical test methods, multivariate methods)

Applied programming (Semester II)

  • Basics and application of Programming languages for Big data: SQL, R and Python
  • Languages & tools for data management
  • Data integration
  • ETL vs. ELT (Data Lake)

Analysis of semi- & unstructured data (Semester II)

  • Crawling and preprocessing
  • Text Mining / Web Mining
  • Social media analysis
  • Ontologies
  • Semantic and graphic
  • Modeling / technologies

Leadership & Sustainability (Semester II)

  • Leadership as part of the normative, strategic and operational business management and in context of diversity management
  • Leadership styles, techniques and instruments Ethics and sustainability

Project Management of big data projects (Semester III)

  • Planning, controlling & controlling Big Data projects
  • Challenges, Special Features & Success factors in the management of Big Data projects
  • Architectural and technological features
  • Introduction of big data applications
  • Integration and harmonization of data sources and planning of data analysis and reporting

Big Data Analysis Project (Semester III)

  • Selection of an application field for the analysis project
  • Project work with first completely own data analysis

Application fields Business Analytics (Semester III)

  • Goals and responsibilities for Big Data applications
  • Sector and type of data sources
  • Application of procedures such as association analysis, Decision tree procedure, neural networks, cluster analysis

Ethics & Law (Semester IV)

  • Ethical aspects of using big data
  • Legal aspects of big data usage
  • Compliance

Big Data Consulting Project (Semester IV)

  • Selection of an application field for the analysis project
  • Data storytelling
  • Addressing a management question
  • Data acquisition, processing, & analysis
  • Preparation of the insights for the management

Strategic business model development (Semester IV)

  • Results of big data analysis as a driver for the Business Model Development
  • Planning the Big Data strategy / business analytics strategy
  • Strategic approaches and strategic planning and management tools
  • Data-based business models and business transformation
  • Open Innovation / Innovation Management


The FOM became the first private university in Germany by the FIBAA, the agency for Quality assurance in the university sector, system accredited. These labels show that that has been around for many years Years established, internal quality management system of FOM meets the standards of the Accreditation Council. FIBAA acknowledges that FOM can independently ensure the quality of its study programs.

Thus, all programs offered by the FOM are accredited. Basically, the FOM certifies that, they have excellent academic qualifications and very good study conditions - especially for working students - and thus ensures the employability of their graduates. To the special The strengths of the FOM also include the competence-oriented teaching that meets the needs of the market.

Salient Features

Students would be given an Macbook Air at the beginning of the first year

Courses taught by faculties with International Exposure.

Industrial visits would be part of the study every semester (2 industries / semester )

Two days of outbound training for all the students at the beginning of the first year (to inculcate team spirit and better understanding of each other)

Uniforms for each student consisting of 2 trousers, 2 shirts and a tie every year. ( one Blazer at the beginning of the first year)

The fee payable is inclusive of all the other statutory payments towards the university(Hostel fee separate)

All students are eligible to get Educational Loan at NO-COST EMI. Students can pay fee on monthly basis.

Free access to quality management e-books and journals.