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Big Data & Business Analytics

Master of Science (M.Sc.)

Degree: Master of Science (M.Sc.)

Master’s Study Programme Big Data & Business Analytics

When is the appropriate time to introduce products? Which audiences should be targeted? Should we invest in new production lines?

Big Data is becoming increasingly more important in business practice: from finance to the health sector, the amount of structured and unstructured data that companies are providing nowadays is rapidly increasing. Big Data specialists bridge the gap between logic and quantitative methods, programming languages, frameworks and infrastructure, all the way to the interpretation and implementation of the results in business processes.

There is high demand for Big Data analysts in companies. Therefore, the FOM Hochschule has developed a study programme, which focuses on the corporate value of data. From the winter semester 2018 onwards, (economic-) programmers, engineers, and scientists, as well as mathematicians and statisticians, can enrol in the new Master’s programme “Big Data & Business Analytics”.

The Master’s degree in Big Data & Business Analytics will be completed with the academic degree Master of Science (M.Sc.). The degree will be awarded by FOM Hochschule für Oekonomie & Management.

Duration

4 Semester inclusive Thesis

Accreditation (Master)

The FOM University of Applied Sciences is accredited by the German Council for Science and Humanities for its special service to education and research and was the first private university in Germany to receive system-accreditation by the FIBAA in 2012. This seal of approval proves that the quality management of the FOM University meets the high standards of the Accreditation Council, the most important body for the quality of studies and education at German universities. In 2018 the FOM University received system-accreditation for further eight years. Thus, all courses of study offered by the FOM are accredited. A Master’s degree from the FOM University enables entry to a subsequent a PhD programme.
Multi-ethnic group of students sitting at desk in lecture hall of modern college and smiling happily, focus on young Middle-Eastern man wearing glasses, copy space

Studying full-time in India and Germany

Master’s degree on campus

In cooperation with FOM Hochschule, students from India now also have the opportunity to participate in the Big Data & Business Analytics Master’s programme at the Asia-Pacific Institute of Global Studies in New Dehli, India.

The first two semesters of the study programme will be held at the Asia-Pacific Institute of Global Studies in India, and the third and fourth semester will take place at the FOM Hochschule at the German University Center in Essen, Germany.

What you need for admission

Bachelor's degree

with at least 60 credit points in (Economic-) Computer Science modules

or

with least 60 credit points in subject related modules (for example, Mathematics, Statistics)

or

successfully completed oral and written admission examination

English language B2


All information on registration and tuition fees can be found on Asia-Pacific Institute of International Programmes website.

 Partner website
Mr. A.K. Shrivastava
Hon'ble Chairman, Asia-Pacific Institute of Global Studies, New Delhi, Delhi, India
+91 8800 025113
admission@asiapacificeducation.org

Semester Overview

Study programme

Big Data Architecture & Infrastructure

Enterprise architecture management (EAM)
Technological requirements for big data
Vital infrastructures for data-driven business models
Complex processing by continuous data sets

Decision Focussed Management

Traditional decision theory
Management decisions from a psychological perspective
Decisions in a strategy context

Leadership & Sustainability

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

Big Data Analytics

Data sources and data classification
Visual analytics/data discovery/explorative data analysis
AI methods such as machine learning
Computational intelligence: fuzzy logic, neuronal networks, evolutionary algorithms

IT-Security

Data protection and data privacy
Risk analysis/type of threats
Attack vectors and scenarios
IT security guidelines

Applied Programming

Basic principles and application of programming languages for big data: SQL, R and Python
Languages and tools for data management
Data integration
ETL v. ELT (data lake)

Analysis of Semi- & Unstructured Data

Crawling and pre-processing
Text mining/web mining
Social media analysis
Ontologies
Semantic and graphic modelling/technologies

Project Management of Big Data Projects

Planning, management and control of big data projects
Challenges, specific features and success factors of big data project management
Architectural and technological features
Introduction of Big Data applications
Integration and harmonisation of data sources and planning of data analyses and reporting

Area of Application: Business Analytics

Goals and fields of activity for big data applications
Sector and type of data sources
Application of processes such as association analysis, decision tree process, neuronal networks, cluster analysis

Ethics & Law

Ethical aspects of the use of big data
Legal aspects of the use of big data
Compliance

Deutsch

Fundamentals in listening, reading, writing and speaking
Basic grammatical skills
Application in situations of everyday life

Big Data Consulting Project

Selection of an area of application for the analysis project
Data storytelling
Addressing a management issue
Data acquisition, processing and analysis
Preparing findings for management

Quantitative Data Analysis

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

Big Data Analysis Project

Selection of an area of application for the analysis project
Project work with first independently produced data analysis

Strategic Business Model Development

Results of big data analyses as drivers of business model development
Planning of big data strategy/business analytics strategy
Strategy approaches and strategic planning and management instruments
Data-based business models and business transformation
Open innovation/innovation management

Applied Project I

Master Thesis

Applied Project II

Subject to change.